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(Continued on the inside back cover.) 95 = World Bank Discussion Papers Education and D evelopment
Evidence for New Priorities
Wadi D. Haddad, Martin Carnoy, Rosemary Rinaldi, and Omporn Regel
The World Bank Washington, D.C. Copyright C 1990 The International Bank for Reconstruction and Development/THE WORLD BANK 1818 H Street, N.W. Washington, D.C. 20433, U.S.A.
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ISSN: 0259-210X
Wadi D. Haddad is senior education adviser, Rosemary Rinaldi an operations analyst, and Omporn Regel a research analystin the World Bank's Population and Human Resources Department, to which Martin Camoy is a consultant.
Library of Congress Cataloging-in-Publication Data Education and development : evidence for new priorities / Wadi D. Haddad ... [et al.]. p. cm. -- (World Bank discussion papers ; 95) Includes bibliographical references. ISBN 0-8213-1624-9 1. Education--Economic aspects. I. Haddad, Wadi. II. Series. LC65.E314 1990 338.4'737--dc2O 90-41324 CIP Table of Contents
Introduction ...... 1
The Contribution of Education to Economic and Social Development ...... 3
Education and Economic Growth ...... 3 Education and Productivity ...... 4 Benefit-Cost Analysis ...... 5 The Education of Women ...... l0...... Education and Poverty ...... 15
Trends in Educational Development ...... 19
Trends in Educational Enrollments ...... 19 The Educational Spending Crisis ...... 33
Lessons from World Bank and Other Donor Experience in Education and Training ...... 37
Total Education Sector Lending by Multilateral and Bilateral Agencies ...... 37 History of Bank Investments in Education and Training ...... 37 Education and Training Department/Division Reviews: Reviews of Education and Training Operations ...... 41 Education and Training Department/Division Reviews: Reviews of Sectoral Performance ...... 42 Operations Evaluation Department Reviews: Reviews of Project Performance ...... 42 Operations Evaluation Department Reviews: Reviews of Sectoral Performance ...... 42 Education Sector Performance Review by Other Donor Agencies ...... 42
Policy Issues and Directions ...... 45
Vocational and AcademnicSecondary Education ...... 45 The Quality and Efficiency of Education ...... 49 Technology in Education ...... 56 Sector Management ...... 56 Science Education ...... 58 Higher Education, Scientific Research and Development, and Technology Transfer ...... 58 Educational Finance Reform...... 60 Conclusion ...... 67
Where More Work is Needed ...... 67 Education and the Changing International Division of Labor ...... 67 The Knowledge Gap ...... 68 Nations Face a Variety of Educational Problems Demanding Different Strategies ...... 69
Bibliography ...... 73
Tables
1 Education and Productivity: Empirical Studies in Selected Countries. 5 2 Rates of Return to Males' Education. 7 3 Rates of Return to Males' Education, by Level of Development .10 4 Male-Female Enrollment Ratio Gap, by Income Level and by Level of Education .11 5 Educational Participation and Women's Achievement: Selected Empirical Studies in Developing Countries .13 6 Gender Comparisons: Male-Female Labor Force Participation and Adult Literacy .13 7 Rates of Return to Education by Gender .14 8 Education, Mortality, Nutrition and Fertility: Selected Empirical Studies in Developing Countries .16 9 Total Enrollment and Growth, 1960-1984 .21 10 Out-of-School 6 to 1 1-Year-Olds in Low-Income and Lower-Middle Income Countries .25 1 1 Retention Rates by Income Level .26 12 Public Recurrent Expenditures on Education as a Percentage of GNP .27 13 Public Expenditures on Education as a Percentage of Total Government Expenditures .28 14 Public Recurrent Expenditures on Education per Pupil .29 15 Public Recurrent Expenditures on Education per Pupil as a Percentage of GNP Per Capita .32 16 Comparative Flow of Education Aid, 1980-1986.38 17 Distribution of Lending for Education and Training by Region .38 18 Distribution of Investments by Type of Curricula and Level of Education . 39 19 Patterns of Education Project Expenditures .39 20 Education Subsector Reviews .39 21 Reviews of Bank Experience in the Education Sector .40 22 OED Project Completion/Audit Reports in the Education Sector .41 23 Evaluation Reports on Education and Training Activities Available from Other Agencies .43 24 Vocational-Technical Education and Training Versus Academic Education: Selected Empirical Studies in Developing Countries .46 25 Improving the Quality of Education: Selected Empirical Studies in Developing Countries .51 26 Education and Technology: Selected Empirical Studies in Developing Countries .53 27 Improving Sector Management: Selected Empirical Studies in Developing Countries .56 28 Scientific and Technical Personnel by Level of Development .62 29 Share of Cumulative Public Educational Expenditure Appropriated by Various Socioeconomic Groups, 1980 ...... 64 30 Alternative Financing Approaches: Selected Empirical Studies of Cost Recovery and Private Education in Developing Countries ...... 65
Figures
1 Females as a Percentage of Total Enrollment, 1984 ...... 12 2 Total Enrollment, 1960-1984 ...... 20 3a Primary School Enrollment Rates, 1960-1985 ...... 24 3b Secondary School Enrollment Rates, 1960-1985 ...... 24 4 Retention Rates by Income Level ...... 25
1 Introduction
1.1 Education has been recognized as a cornerstone of economic and social development. More recently, however, it has become even more important to the development process as accelerated technological change and new organizations of production transform the world economy. Information, biological enhancement, and new materials -- more than machines or labor alone -- are the bases of new sources of wealth. Development in all its forms -- economic, social, and cultural -- will depend increasingly on knowledge-intensive industries, agriculture, and services. Education is a key to developing that knowledge and the sense of personal efficacy needed to adjust to rapid change.
1.2 Although these new conditions place new demands on the educational system world- wide, the continuing economic crisis has jeopardized the ability of many countries even to maintain the present levels and quality of their educational services. The 'knowledge gap" -- the disparity in the capability of countries or groups within countries to participate in the gains of technological innovations and new production processes -- is growing. Many countries are falling farther behind in providing the education and training needed by their youth to create and adapt available knowledge to their environment. A widening gap has serious implications for the future economic development of those countries falling behind. It guarantees that they will be increasingly hindered in efforts to enhance and shape their own economic and social development process. Their already low standard of living could also fall.
1.3 These new conditions suggest a new message. There is a need for more and better education in all countries -- industrialized and less-industrialized, high-income and low- income. Providing universal primary schooling in India or reducing high school dropouts in the United States is each a crucial development issue in that particular society. Developing the cadre of scientific and technical personnel to lead the country into an age of transformation in information, biological, and materials sciences is important in France and Zimbabwe. But the rapid changes in the world economy and the growing gap between rich nations and poor also suggest that not all countries face the same educational problems. All countries should be striving to increase student learning and to equalize access to knowledge, and all can learn from each other in using educational techniques that work. But lower-income countries with high rates of illiteracy and children out of school may also require qualitatively different approaches to improving and expanding schools than those possible in higher-income coun- tries with much higher average schooling levels and more resources.
1.4 Detailed data on the major areas of educational policy and practices are available to produce a new analysis of these challenges and to recommend coherent, practical policies for the future. The World Bank has been active in this field for 25 years, other international agencies such as UNESCO have collected massive amounts of data, many countries have been investigating their own education at a national and comparative level, and individual scholars worldwide have also produced a wealth of educational research. Three decades of educational
Education and Development: Evidence for New Priorities I 2 Education and Development: Evidence for New Priorities analysis and investment -- much of it by the Bank -- provide a solid base for understanding the relationship between education and economic development, for analyzing the contribution of various levels and types of education, for evaluating measures to improve the quality of educa- tion, for assessing the successes and failures of past educational policies, and for suggesting concrete alternatives for countries facing different economic and educational conditions, to cope with the changed circumstances of the 1990s.
1.5 The World Bank plays a singularly important role in international lending for educa- tion. In many countries the Bank is the major source of educational advice, and other agencies increasingly follow the Bank's lead in such policy and lending. Therefore, its experiences carry particularly significant weight in how educational development and lending proceeds worldwide. An analysis of these experiences, past educational policies, and new directions for policy would make an important impact on educational change -- hence economic develop- ment -- in the coming decade.
1.6 This is therefore a particularly opportune moment for taking a fresh look at educa- tional development and donor educational policy.
1.7 In order to address these themes on education, an extensive bibliographical review was carried out and available statistics, research results, and policy studies were scanned. Not only has there been an enormous body of statistics compiled by UNESCO and other agencies over the past 25 years on enrollment growth and educational spending and costs, but the World Bank and other intemational and bilateral lenders have amply documented and analyzed their vast experience in financing educational projects. In addition, these same lenders and academ- ics have carried out hundreds of research studies on various aspects of educational policy. For presentation purposes, these available statistics and studies are divided into four sections: (1) The Contribution of Education to Economic and Social Development; (2) Trends in Educa- tional Development; (3) Lessons from World Bank and Other Donor Experience in Assisting Education; and (4) Policy Issues and Directions. Data availability in each of these categories is assessed below. An extensive bibliography is also attached (pages 73-99). 2 The Contribution of Education to Economic and Social Development
2.1 There is now a persuasive body of theoretical and empirical evidence that investment in the formal education and training of the labor force plays a crucial role in economic development. The empirical evidence takes five main forms: (1) Growth accounting studies, which estimate the contribution to economic growth in a given time period of investment in the education of the labor force. (2) Productivity studies, which estimate the contribution of additional education to the physical productivity of workers and farmers. (3) Benefit-cost studies, which evaluate the economic contribution of formal eduction and training in terms of their private costs (earnings foregone and other expenses incurred by students while in school) and public costs, and the additional income earned by those who take the education and training. (4) Studies which estimate womens' educations' effect on long-term economic development and quality of life. (5) Studies that estimate the role of education in poverty alleviation.
2.2 The results of these studies suggest that in both developed and developing countries, educational investment has been one of the most important factors contributing to economic growth; that expenditures on education contribute positively to labor productivity; that the economic payoff to spending on education -- from both a private and public standpoint -- is high, in absolute terms and compared to other investments; and that increased education of parents -- especially mothers -- has an important impact on child health and reduced fertility at all levels of economic development.
Education and Economic Growth
2.3 Some of the earliest research on the relationship between education and economic development focused on the contribution of education to economic growth (Schultz, 1961; Denison, 1962; 1967). These attempted to account for the unexplained "residual" growth left when only changes in labor (hours worked per year) and physical capital were included in the production function (Solow, 1957). Denison found that between 1930 and 1960, 23 percent of the increase in the United States' output was due to the increased education of its labor force. Further growth accounting estimates for the United States and Europe in 1950-1962 showed a wide variation for education's contribution, from a low 2 percent in Germany to highs of 12 percent in the United Kingdom, 14 percent in Belgium, 15 percent in the United States, and 25 percent in Canada. Similar estimates for developing countries also suggest a wide variation of educational contribution, from lows of 1 to 3 percent in Mexico, Brazil, and Venezuela to 16 percent in Argentina. Other estimates for Ghana, Kenya, Nigeria, Malaysia, and the Republic of Korea, based on Schultz's method, show an education contribution in the 12 to 23 percent range (see Psacharopoulos and Woodhall, 1985, Table 2-1).
2.4 Growth accounting does not provide a criterion for educational investment policy, since it only shows that should economic growth occur simultaneously with a considerable
Education and Development: Evidence for New Priorities 3 4 Education and Development: Evidence for New Priorities investment in education, educational investment will account for a significant percentage of that growth. But these studies do suggest, for all their limitations, that a number of countries have achieved high economic growth with large investments in education. Furthermore, other studies, discussed below, imply that unless the indirect effects of education -- such as those on health and fertility -- are accounted for, the total impact of education on growth may be underestimated.
Education and Productivity
2.5 The single best measure of education or training's economic impact is the additional productivity of workers and farmers with more education and training over those with less. Productivity measures avoid the pitfalls associated with using earnings as a proxy for eco- nomic contribution, particularly in labor markets that are highly non-competitive, marked by barriers to entry and other distortions. But productivity comparisons are hard to come by (Metcalf, 1985) and estimating the relationship between education and productivity is beset by limitations -- individuals with different amounts of education are generally in different types of jobs, producing different products.
2.6 Nevertheless, there is evidence that education results in higher output (see Table 1, page 5). A survey for the World Bank of eighteen studies which measure the relationship in low-income countries between farmers' education and their agricultural efficiency (as measured by crop production) concluded that if a farmer had completed four years of elementary education, his productivity was, on the average, 8.7 percent higher than that of a farmer with no education (Lockheed, Jamison and Lau, 1980). This is an average of results from 31 data sets, which yield both negative and highly positive education effects (a standard deviation of 9 percent). The survey also found that the effect of education is higher where complementary inputs are available. Further evidence on the effect of education in raising farmers' productivity appears in World Bank studies carried out in the Republic of Korea, Malaysia and Thailand (Jamison and Lau, 1982), and more recently in Nepal and again in Thailand (Jamison and Moock, 1984). Other studies (for example, Sack, Camoy, and Lecaros, 1980), although reporting mixed results, support the general conclusion that educa- tioncontributes positively to agricultural productivity, especially where other inputs are avail- able to farmers and land reform has created favorable conditions for a range of production choices.
2.7 A few attempts have also been made to analyze the effect of education on productiv- ity in industry (for a review, see Berry, 1980; also see Fuller, 1970; Min, 1987). Berry's review suggests that there is little conclusive evidence that education has a positive effect on productivity in urban areas. Fuller's research in two electrical machinery factories in Bangalore, India shows that there is a positive effect of education and training on output, especially when that training is in-firm. Min's study of academically and vocationally- educated workers in a Chinese automobile factory also shows a small, but statistically significant, increase in productivity associated with more education, and a 6 to 11 percent higher productivity for those with vocational schooling than for those with academic schooling.
2.8 The main reason that it is so difficult to get significant results in urban areas is that such studies (and those in agriculture as well [see Sack, Carnoy, and Lecaros, 1980]) is that they necessarily measure productivity-education relations in a single occupation. But the main payoff to additional education is the opportunity to move into higher-paying occupations. Workers with higher than average levels of education in a given occupation are not represen- tative of all workers within that level, since more motivated workers with these higher levels of education have moved into higher paying jobs. Thus, such studies tend to underestimate the payoff to more education. In that sense, wage differences may provide a more accurate picture Education and Development: Evidence for New Priorities 5
Table 1. Education and Productivity: Empirical Studies in Selected Countries
Study Data Base Results
Patrick and Five agriculturalregions Educationhas a positive and significant Kehrberg(1973) in Brazil in 1969, effect. Value added in agriculturein individualfarmers modernizingareas, but not in traditional and already modernareas.
Pachico and Four agriculturalregions Additionalproductivity associated with Ashby (1976) in Brazil in 1970, more educationmuch higher in the individualfarmers two modernizingzones, where addi- tional, non-educationalinputs are available.
Lockheed, Survey of 18 studies, A farmnerwith 4 years of educationhad Jamison,and meta-analysis an averageproductivity 8.7 percent Lau (1980) higher than one with no education.With complementaryinputs, return was higher (13 percent).
Jamison and Surveydata on types Effect of education on output is positive, Lau (1982) of farms, educationof significant,and quantitativelyimportant. farmer,physical inputs, and outputs in Korea, Malaysia,and Thailand
Jamisonand Data on prices of farm No significanteffect of education on Moock (1984) inputs and outputsin prices farmersreceive for output or Thailand or paid for inputs.
Jamisonand Survey of 683 rural Significanteffect of educationon farmer Moock (1984) householdsin 2 of Nepal's efficiencyonly in wheat production. 75 districts. Abilityand familybackground controlled for.
Fuller (1970) Surveyof workersin two In-plant vocationaltraining yields higher electricalmachinery productivityincreases than factoriesin Bangalore, institutionalvocational education. India, 1970
Berry (1980) Surveyof productivity Resultsof such studies are inconclusive. studies on urban workers
Min (1987) Surveyof workersin Workerswith vocationaleducation have Beijing, China auto factory 7 percenthigher productivitythan workerswith academic education. More years of educationnot significant.
of the returns to education, although productivity studies may still be useful to measure the payoff to vocational versus academic education.
Benefit-Cost Analysis
2.9 We now have benefit-cost and rate of return analyses for a large number of countries, and at different points in time (Psacharopoulos, 1985). They suggest that the economic payoff 6 Education and Development: Evidence for New Priorities to education is high and remains high with economic growth even as educational systems expand (see Table 2 and Table 3, pages 7 and 10).
2.10 The economic appraisal of investment projects by the World Bank and other development agencies is based on calculations of the net present value of projects and also on calculations of the rate of return. The argument for the applicability of these calculations to education and how rates of return to education are estimated has been made in a number of places (for example, Blaug, 1970; Thias and Camoy, 1972; Psacharopoulos and Woodhall, 1985). The general consensus is that although there are a number of problems with many of the empirical estimates of rates of return -- particularly in the way costs of education are measured, the fact that the samples used for the estimates are usually drawn only from the urban labor force, and that the rates of return are uncorrected for ability differences, social class differences, and unemployment differences among those with different amounts of edu- cation -- the rates still give us important insights into the relative economic payoff to education and different levels of education in different countries at different levels of development. More recent estimates of rates of return to education at different points in time in the same country (Camoy and Marenbach, 1975; Psacharopoulos and Woodhall, 1985; Carnoy, Daley, and Hinojosa, 1988; Ryoo, 1988) give us additional insights into the changing payoffs to educational investment as countries expand their economies and educational systems.
2.11 In Table 2, rate of return estimates are shown for a large number of developed and developing countries. Where more than one estimate has been made for the same country, each estimate is shown separately, by year. The countries have been divided by level of economic development [as measured (approximately) by a number of criteria (gross domestic product per capita; absolute GDP; percent of GDP in manufacturing; percent manufactured exports; percent high-tech manufactured exports; percent females in the labor force)] into five groups: (a) industrialized, high-income economies; (b) newly-industrialized, developing economies (NICs), involved in high-tech manufacturing and sophisticated industrial exports plus high-income oil exporters; (c) middle-income, industrializing developing countries which are or are about to participate in the world high-tech production system (although India is a low-income country, it is included in this category because of the very size of its industrial base); (d) marginally industrialized, middle-income countries that are not presently or barely involved in the changes taking place in the world economy; and (e) primarily agricultural, lower-income countries.
2.12 These categories are somewhat arbitrary and most of the rates were estimated in the 1970s, when some countries were at much lower levels of development. But the division suggests: (1) that the highest overall social rates of return to education (in urban areas) are generally in the lower income, agricultural economies and in the marginally industrialized economies; (2) that the highest payoff to education in these lower-income and middle-income countries is at the primary level; and (3) that as countries industrialize, increase their GDP per capita, and invest more in education, rates of return to education tend to fall overall, and the payoff to lower education levels tends to fall relative to the payoff to higher education levels.
2.13 Furthermore, the gap between private rates of return to education and the social rates is highest in the lower and marginally industrialized middle-income countries (see Table 3). Given the high costs of higher education, the gap is particularly striking at the higher educa- tion level. But there also appears to be a large private-social Tate gap at the secondary level in marginally-industrialized, middle-income countries. This has implications for alternatives to financing education, especially in low-income and middle-income countries, where new re- sources for financing education have become scarce as growth rates declined in the 1980s.
2.14 Great care must be taken in making such comparisons, especially given the variation in sampling and cost estimate accuracy among these reported rates. Yet, recent studies of rates Education and Development: Evidencefor New Priorities 7
Table 2. Rates of Return to Males' Education
Country Year Primary Secondary Higher Primary Secondary Higher
Social Rate Private Rate
Group A
Group A Mean' 26 17 12 40 20 32
BurkinaFaso 1970 26 61 1975 28 30 22 1982 20 15 21 Ethiopia 1972 20 19 10 35 23 27 Ghana 1967 18 13 16 24 17 37 Kenya 1971 22 19 9 28 33 31 1980 13 14 Lesotho 1980 11 19 10 16 27 36 Liberia 1983 41 17 8 99 30 17 Malawi 1978 15 1982 15 15 12 16 17 47 Sierra Leone 1971 20 22 10 Somalia 1983 21 10 20 60 13 33 Sudan 1974 8 4 13 15 Tanzania 1982 5 Uganda 1965 66 29 12
GroupB
GroupB Mean a 28 17 13 46 29 26
Botswana 1983 42 41 15 99 76 38 C6ted'Ivoire 1987 26 31 25 Morocco 1970 50 10 13 Nigeria 1966 23 13 17 30 14 34 Pakistan 1975 13 9 8 20 11 27 1979 15 7 9 Paraguay 1982 14 11 13
Group C
Group C Meana 28 13 13 24 1S 19
Colombia 1973 18 15 15 21 1976 25 1981 10 Costa Rica 1974 13 9 26 India 1965 13 16 10 17 19 16 1978 29 14 11 33 20 13 Indonesia 1977 26 16 1978 22 16 15 Peru 1972 47 20 16 1974 34 9 15 1980 41 3 16 Philippines 1971 7 6 8 9 6 9 1977 8 16 Thailand 1970 30 13 11 56 14 14 1972 63 31 18 Turkey 1968 8 24 26 8 Educationand Development: Evidencefor New Priorities
Table 2 (cont.). Rates of Return to Males' Education
Country Year Primary Secondary Higher Primary Secondary Higher
Social Rate Private Rate
Group E
Group E Mean' 16 16 12 24 18 20
Brazil 1970 24 13 25 14 Chile 1959 24 17 12 Greece 1962 6 14 7 14 1977 16 6 4 20 6 6 Hong Kong 1976 15 12 19 25 Israel 1958 16 7 7 27 7 8 Rep of Korea 1967 9 5 1969 11 10 1971 15 9 16 16 1973 12 9 1974 17 15 21 22 1979 11 14 13 19 1980 8 12 1986 9 11 10 18 Malaysia 1978 33 34 Mexico 1963 25 17 23 32 23 39 Singapore 1966 7 18 14 20 25 Taiwan 1970 26 15 18 18 Venezuela 1984 32 12 21 Yugoslavia 1969 9 15 3 8 15 3
Group F
Group F Mean * 10 10 13 12
Australia 1969 14 14 1976 16 8 21 Austria 1981 11 4 Belgium 1960 17 7 21 9 Canada 1961 12 14 16 20 Denmark 1964 8 10 France 1962 14 12 9 1969 10 11 16 12 10 1976 14 11 9 Germany 1964 5 1978 6 11 Great Britain 1971 11 7 14 27 1972 4 8 12 10 1973 8 8 6 16 1975 7 7 9 22 1977 8 6 9 17 1978 9 7 11 23 Italy 1969 17 18 Japan 1967 10 1973 5 6 6 8 1976 10 9 7 13 10 9 1980 6 8 Netherlands 1965 5 6 8 10 New Zealand 1966 19 13 20 15 Education and Development: Evidencefor New Priorities 9
Table 2 (cont.). Rates of Returnto Males' Education
Country Year Primary Secondary Higher Primary Secondary Higher
Social Rate Private Rate
Norway 1966 7 8 7 8 Spain 1971 17 9 13 32 10 16 Sweden 1967 10 9 10 U.S.A. 1939 18 11 1949 14 11 1959 10 11 1969 11 11 19 15 1969 b 14 11 1979 b 18 10 1982 b 24 13 1985 b 22 14
The mean for each group is calculatedby fist estimatinga mean for each countrywhere more than one rate is available,then estimatinga simple arithmeticmean. b Rates from M. Camoy,H. Daley,R. Hinojosa,'The ChangingEconomic Position of Minoritiesand Women in the U.S. Labor Market Since 1959,"Stanford University (mimeo) -- rates are for white males only.
Sources: G. Psacharopoulos,"Returns to Education:A FurtherInternational Update and Implications." Journal of Human Resources,Vol. 20, No. 4 (1985),pp. 583-604;Appendix Table A-1. C6te d'Ivoire: A.G. Komenan, "Education,Experience et Salairesen Cote d'Ivoire,"World Bank DiscussionPaper, June, 1987; Republicof Korea, 1974, 1979,and 1986: J. Ryoo, "Changesin Rates of Returnto Education:A Case Study of Korea."Unpublished Ph.D. Dissertation,Stanford University, 1988. United States.
of return over time in the United States and Korea using large census samples support the tendencies revealed by the cross-sectional data. In the United States, rates to secondary education fell relative to higher education payoffs from 1939 to 1959, stabilized in the tight labor market of the 1960s, rose relative to higher education in the early 1970s (Freeman, 1976; Psacharopoulos, 1980), but continued their secular decline in the late 1970s and 1980s (Camoy, Daley, and Hinojosa, 1988). The Korean rates show a similar relative decline of secondary rates between 1974 and 1986 (Ryoo, 1988). Ryoo's estimates confirm the trend in other estimates for that country.
2.15 Despite the tendency for the average rate of return to education to fall with economic development, rates stay high compared to altemative investments. The main implications for policy lie in the changing structure of rates to different levels of schools as countries expand their economies and educational systems. It is not surprising that as countries industrialize and achieve universal primary education and large fractions of young people attending secondary school, the payoff to primary education falls relative to secondary and higher education. And as economies move into high levels of industrialization and universal secondary education, the payoff to that level falls relative to university. Although serious problems in the quality of primary and secondary education may continue to exist even when it is universal (in the United States, for example), the payoff to expanding access to those levels is likely lower than to expanding university. [We discuss the payoff to quality of education in more detail on page 49.] All this suggests that economies at different levels of development face very differ- ent educational investment problems and choices. 10 Education and Development: Evidence for New Priorities
Table 3. Rates of Returnto Males' Education,by Levelof Development
Level of Education
Primary Secondary Higher Primary Secondary Higher
Level of Development Social Rates PrivateRates
PrimaryProduct, Low-Income 26 17 12 40 20 32
MarginalIndustrial, Middle-Income 28 17 13 46 29 26
Industrializing, Middle-Income, High Education 28 13 13 24 15 19
Newly-Industrialized 16 16 12 24 18 20
Industrialized n.a. 10 10 n.a. 13 12
The Education of Women
2.16 Young women get less education than young men in almost every country. A recent World Bank study found that in the last thirty years, women in developing countries have increased their average years of schooling by about 0.6 years more than males have (Horn and Arriagada, 1986), but despite this increase, women's enrollment in primary and secondary education is lower than that of men by at least ten percentage points in 66 of 108 countries and is higher in only eight countries (Sivard, 1985). The gap is the greatest in the low-income countries and lowest in the upper-middle and high-income countries, increasing in higher levels of education (see Table 4, page 11; and Figure 1, page 12). Among areas of the world, the female-male gap is the highest in the Middle East/North Africa and the lowest in Latin America, followed by Eastem Africa.
2.17 A review of 80 empirical studies on the determinants of educational participation and achievement of women in developing countries (Stromquist, 1988) suggests that family eco- nomic conditions are more important than school-related variables (such as distance from school, adequate sanitary facilities, and the existence of a library) in explaining this gap (see also, Bowman and Anderson, in Kelly and Elliott, 1982). The poorer the household, the greater the tendency for parents to rely on daughters for domestic duties and to save educa- tional investments for their sons. Cultural and religious factors such as early marriage and rigid rules that define women strictly as mothers and wives affect both girls' enrollment and their length of schooling (see also, Smock, 1981). This is especially true in low-income countries, in low-income regions, and in rural areas, reflecting the strongly negative interactive impact on girls education of religion and low socioeconomic class. Furthermore, the behavior of the school and the family reinforce each other, not in explicit actions but by failing to take steps to combat gender asymmetries. The school does not encourage families to send daugh- ters to school, and the parents and communities do not pressure schools to offer suitable facilities and learning experiences for their daughters. As Stromquist points out, the state is the crucial actor for change. Without explicit government policies to promote the equal schooling of girls (including the provision of adequate facilities), it is unlikely that family practices will be changed. Education and Development: Evidence for New Priorities 11
Table 4. Male-Female Enrolment Ratio Gap by Income Level and by Level of Education
TotalEnrollment (M+F) % Gap
1960 1970 1980 1984 1960 1970 1980 1984
Primary
Low Income Countries 145,411 191,527 277,024 270,797 (W) 26.0 26.0 16.0 12.0 (U) 41.4 32.0 20.6 21.8
Lower-MiddleIncome Countries 37,242 60,654 95,442 105,692 (W) 14.0 12.0 8.0 4.0 (U) 18.2 15.4 10.4 4.2
Upper-MiddleIncome Countries 42,838 63,408 83,283 88,385 (W) 6.0 6.0 4.0 4.0 (U) 7.8 6.8 3.6 4.4
HighIncome Countries 69,693 68,377 65,962 63,385 (W) 2.0 2.0 4.0 2.0 (U) 10.8 10.8 4.6 3.2
Secondary
Low Income Countries 26,993 51,337 98,425 99,564 (W) 56.0 44.0 24.0 22.0 (U) 62.0 50.6 39.0 44.0
Lower-MiddleIncome Countries 3,950 12,000 25,747 31,915 (W) 32.0 30.0 16.0 6.0 (U) 33.6 27.0 17.2 4.6
Upper-MiddleIncome Countries 8,753 20,552 26,363 35,821 (W) 16.0 12.0 6.0 6.0 (U) 13.6 12.6 5.8 2.2
High Income Countries 28,443 49,948 54,966 57,588 (W) 4.0 4.0 0.0 2.0 (U) 18.6 10.4 5.0 4.0
Tertiary
Low Income Countries 2,125 3,333 7,119 8,485 (W) 60.0 68.0 56.0 48.0 (U) 74.0 67.6 55.6 58.0
Lower-MiddleIncome Countries 658 1,912 4,435 6,645 (W) 30.0 26.0 16.0 26.0 (U) 59.3 52.4 30.8 19.6
Upper-MiddleIncome Countries 1,233 2,905 6,373 7,691 (W) 40.0 28.0 14.0 18.0 (U) 38.4 28.6 13.8 13.0
High Income Countries 5,883 14,079 20,768 22,115 (W) 34.0 24.0 6.0 22.0 (U) 39.2 32.6 16.2 12.0
Note: (W) - WeightedMean (U) - UnweightedMean 12 Education and Development: Evidence for New Priorities
Figure 1. Females as a Percentage of Total Enrollment, 1984
Percent 50
40 -
30
20
10
0 Primary Secondary Tertiary
Low-income Lower-Middle Income [ Upper-Middle Income 9 High Income
2.18 Why is it important to increase female education? Besides the obvious equity argument, it is now evident from the accumulated evidence that when women receive low levels of education, it hinders economic development and reinforces social inequality (Table 5 has a review of two empirical studies on the determinants of women's educational achieve- ment and on the role of education in women's labor force participation and income; Table 6 lists female labor force participation and adult literacy, by country in 1960 and 1980).
2.19 Women represent an enormous potential source of human capital and of scientific and technical skills in both agriculture and industry. The rate of return to investing in women's education in developing countries is as high or higher, even as measured by income differ- ences alone (without accounting for fertility and child health effects), as men's (see Table 7; Psacharopoulos and Woodhall, 1985; Ryoo, 1988).
2.20 Women constitute an important source of skills in rapidly expanding electronic and communications manufacturing, and financial and computer services (Camoy, 1985). It could be argued that the existence of a well-educated female labor force with industrial experience is the single most important factor governing the location of high-tech industry and services. Whereas these are highly gender-segregated industries in both developed and developing countries (Strober and Arnold, 1987; Kim, 1987), they do provide non-agricultural occupational opportunities for women and appear to contribute to changing male-female relations in the NICs (Kim, 1987). The lack of an educated female labor force could seriously hinder industrializing countries with high female illiteracy from participating in high-tech industrialization. Education and Development: Evidence for New Priorities 13
Table 5. Educational Participation and Women's Achievement: Selected Empirical Studies in Developing Countries
Study Data Base Results
Stromquist (1988) Eighty available Family economic conditions are impor- empirical studies tant in affecting women's education, with poorer households tending to keep daughters at home. Cultural and religious factors affect both girls' enrollment and length of schooling, but religion seems neutralized as parents income and educa- tion increases.
Sivard (1985) Review of world- In most of world, increased participation wide statistics on of women in wage labor in 1960-80. But women's labor force women's unemployment higher, wages and educational lower than men's. Women are characteristics segregated in women's jobs. Agriculture is still principal employer of women in de- veloping countries. Women are much poorer than men.
Table 6. Gender Comparisons: Male-Female Labor Force Participation and Adult Literacy
Labor Force Participation Adult Literacy
Ratio of Ratio of Women's Women's Rate Rate 1980 1960 1980 to Men's 1960 1980 to Men's GNP Rate Rate Rate Rate per - 1960 1980 1960 1980 capita Wom. Men Woom.Men (Men= Worn.Men Wom. Men (Men= Region (US$) (%) (%) (%) (%) 100%) (%) (%) (%) (%) 100%)
World 2,621 47 90 46 85 52 54 59 68 68 78 87 87
America North America 11,233 41 88 50 83 47 60 98 97 99 99 101 100 Latin America 2,172 21 90 25 84 23 30 63 70 81 85 90 95
Europe Western Europe 9,840 37 91 43 85 41 51 93 96 97 98 97 99 Eastern Europe & USSR 4,480 67 88 69 82 76 84 94 97 97 99 97 98
Asia Middle East3,046 31 91 25 85 34 29 15 39 46 71 38 65 South Asia 226 39 91 36 85 43 42 13 40 31 56 32 55 Far East 1,045 57 90 53 86 63 62 60 77 81 90 78 90 Oceania 8,102 37 92 46 87 40 53 90 91 91 93 99 98
Africa 806 44 92 42 88 48 48 12 27 36 57 44 63
Source: "Women ... A World Survey." R.L. Sivard, 1985. 14 Education and Development: Evidence for New Priorities
Table 7. Rates of Returnto Educationby Gender
Country Year EducationalLevel Men Women
Australia 1976 University 21.1 21.2 Austria 1981 All 10.3 13.5 Colombia 1973 All-urban 18.1 20.8 -rural 10.3 20.1 Costa Rica 1974 All 14.7 14.7 France 1969 Secondary 13.9 15.9 University 22.5 13.8 1976 Secondary 14.8 16.2 University 20.0 12.7 Germany 1974 All 13.1 11.2 1977 All 13.6 11.7 GreatBritain 1971 Secondary 10.0 8.0 University 8.0 12.0 Greece 1977 All 4.7 4.5 Japan 1976 University 6.9 6.9 1980 University 5.7 5.8 Peru a 1985 Primary 12.0 Secondary,Gen. 8.0 Secondary,Tech. 8.5 University 15.5 South Korea 1971 Secondary 13.7 16.9 University 15.7 22.9 1976 All 10.3 1.7 1980 All 17.2 5.0 Sri Lanka 1981 All 6.9 7.9 Portugal 1977 All 7.5 8.4 Puerto Rico 1959 Primary 29.5 18.4 Secondary 27.3 40.8 University 21.9 9.0 Taiwan 1982 Primary 8.4 16.1 Thailand 1971 All 9.1 13.0 Venezuela 1984 All 9.9 13.5
a E. King, 'Does Education Pay in the Labor Market? Women's Labor Force Participation, Occupation, and Earnings in Peru," The World Bank, September, 1988 (mimeo).
Source: Psacharopoulos (1985) "Returns to Education: A Further International Update and Implications," Journal of Human Resources XX:4.
2.21 Rapid population growth has made raising the standard of living in many countries difficult. A bulging population of young people also strains education budgets and, in many low-income countries an increasing absolute number of young people get no education at all. These are the children of rural and low-income families, implying increasing disparities between urban and rural areas and between an emerging urban middle class and the poor. Reducing fertility rates is therefore an important part of any development program, and reduced fertility depends heavily on women's education (Cochrane, 1979) where, particularly in low-income (low literacy) countries, education levels for men and especially women have to reach a "threshold" in order to have a negative effect on fertility. These results are largely confirmed by cross-national studies of world fertility survey data (for example, United Education and Development: Evidence for New Priorities 15
Nations, 1983), except that increasing men's and women's education are equally good explain- ers of declining fertility rates. The analysis also shows a distinct threshold effect in low- income countries at completed primary education (see Table 8, page 16).
2.22 Women's education is closely related to child health, as measured either by nutri- tional status or infant and child mortality (Cochrane. O'Hara and Leslie, 1980). Although the exact mechanism through which education acts to affect child health is unclear, there is an un- equivocal schooling effect which is distinct from the effect of income differences (associated with higher education) on child health (Table 8). Improved child nutrition and health, in tum, plays an important role in school achievement and attainment (Moock and Leslie, 1986). Women's education is therefore crucial to breaking the vicious circle of poverty being repro- duced through poor child health and low levels of education.
Education and Poverty
2.23 From the considerable research in developed countries -- mainly the United States - we know that in and of itself, education cannot eliminate poverty. But by developing skills that individuals can use for increasing their income (either through increased self-employed productivity or increased productivity in wage labor), by contributing to better health, and by reducing fertility, education, especially when combined with investments in other factors of production, can contribute to economic growth, to an increased percentage of the labor force with better-paying work, and the increased standard of living of a smaller family.
2.24 There has been a long debate in the United States on this issue (see, for example, Moynihan, 1967; Ribich, 1968; Thurow, 1970; Sowell, 1977; Smith and Welch, 1986; Camoy, Daley, and Hinojosa, 1988) which -- although specific to the multiethnic nature of society in the United States -- provides insights for developing countries. In brief, U.S. data suggest that increasing education among Black and Hispanic males and females is an important explainer of their rising relative (to non-Hispanic white male) income in a historical period marked by economic growth and somewhat equalizing income distribution. In the late 1970s and 1980s, when economic growth occurred but income distribution in the labor force became signifi- cantly more unequal, rising minority education could not offset declining relative incomes. Nor did the poverty rate decrease with rising education. This implies that education is much more likely to contribute to poverty reduction when there is both economic growth and at least an unchanged income distribution, and at best, an income distribution that is becoming more equal. Therefore, to reduce poverty, the public sector has to invest in education, to plan balanced growth, and to manage an incomes policy that lifts all boats."
2.25 It is important to add that investing in education alone will not equalize income distribution. There is considerable evidence that increasing education in the labor force con- tributes positively to more equal income distribution, but that the effect is small (Langoni, 1973; Chiswick and Mincer, 1972; Camoy, et. al., 1978). Other effects, such as changes in the income distribution itself or, in the case of the United States, unemployment, are far more important. This means that the public sector cannot rely on educational investment alone to equalize income inequality, but rather needs to take other measures, such as sustainable land reform, or the implementation of progressive income-tax based government finance, to achieve this goal. 16 Education and Development: Evidence for New Priorities
Table 8. Education, Mortality, Nutrition and Fertility: Selected Empirical Studies in Developing Countries
Study Data Base Results
Arriaga and Davis Secondary data on Prior to 1930, mortality decline was (1969) Latin American closely related to improvements mortality rates in living standards rather than medical breakthroughs.
Cochrane, et.al, Secondary data on Literacy seems to be most important (1980) mortality rates, by variable explaining life expectancy, country even higher than number of physicians per capita. One additional year of mother's schooling results in reduction of 9 per thousand in infant mortality. Effect of busband's education about one-half of wife's.
Cochrane (1979) Review of existing Increased education tends to decrease studies fertility. Decrease is greater for the education of women than of men and in urban rather than rural areas. But education is likely to increase fertility in countries with the lowest level of female literacy up to completed primary school- ing. In societies with higher levels of female literacy, education lowers the demand for children by altering perceived costs and benefits.
United Nations Data from the world Confirms negative influence of women's (1983) fertility survey of (and husbands') education upon marital 22 developing fertility, desired family size in 20 out of countries 22 countries. But levels of national de- velopment and level of family planning program efforts enhance or mitigate the strength of the education-fertility relationship. Differential fertility by education is highest in the countries with highest levels of development. The negative relationship between education and fertility is stronger in urban areas than rural. Ethnic or regional differences in the education-fertility relationship are not of primary importance.
Zachariah & Patel Fertility decline in Although family planning practice can (1984) India, 1961-1981 account for 90% of fertility decline, family planning input variables -- manpower, budget, etc. -- were much less important than socioeconomic factors such as female education and children's health in explaining the practice of family planning.
Fertility Survey Individuals in For all women married less than of Thailand Thailand 20 years, education is uniformly (1977) inversely related to fertility. Education and Development: Evidence for New Priorities 17
Table 8 (cont.). Education, Mortality, Nutrition and Fertility: Selected Empirical Studies in Developing Countries
Study Data Base Results
Cravioto & Survey in No significantdifference in parental Delicardi Southwestern educationbetween well-nourished (1975) Mexico and malnourishedchildren.
Christiansen,et al. Bogota,Colombia Significantpositive associationbetween (1974) parentaleducation and children's nutrition.
Gans (1963) Lagos, Nigeria Children's weightof literate motherswas greater than illiteratemothers.
Graves(1978) Kathmandu,Nepal Motherswith no schoolinghad more mal- nourishedchildren than those with schooling.
Levinson(1974) Rural Punjab,India Literatemothers had smallerpercentage of third-degreemalnourished children.
3 Trends in Educational Development
3.1 The vast amount of data available from UNESCO and national statistics on trends in educational development provide a detailed picture of the percentage of young people enrolled in primary, secondary vocational, secondary academic, and tertiary levels of education for almost every country from 1960 to 1985. They also provide data on enrollment by gender, retention rates in primary school (or, conversely, drop-out rates), educational spending (recur- rent and capital) as a percentage of GNP and as a percentage of total public spending, and cost- per-student, by education level -- all by country and over time. These data are an excellent source for understanding the educational achievements and difficulties of countries at different levels of economic development.
Trends in Educational Enrollments
3.2 The data show that developing countries have expanded their educational systems rapidly over the past 25 years (see Figure 2, page 20, and Table 9, page 21). From 1960-80, the weighted (heavily influenced by the huge enrollments in China and India) average growth rate of primary enrollment in low-income countries was 3.1 percent annually, and unweighted, 7.1 percent. Secondary enrollments also increased rapidly in the low-income and lower middle-income countries, and the tertiary level grew rapidly in this period at all development levels. But, in the 1980s, the drop in enrollment growth has also been impressive, particularly at the primary and secondary level. Part of this drop is due to slower growth of the school-age population, especially in countries such as China. Yet, for many countries, the drop reflects a real slowdown in incorporating young people into schools.
3.3 The result of the slowdown is that low-income countries are still far from achieving even universal primary education (see Figures 3A and 3B, page 24, for trends in gross enroll- ment rates by level of development). If anything, the gap in gross enrollment rates between the lowest-income countries and the middle-income and developed countries has increased, especially since 1970 and especially at higher levels of education. This gap has become accentuated in the 1980s. Two of the most important exceptions to this trend have been India and China, which -- despite their low levels of income per capita -- have reached enrollment rates at the primary and secondary level associated with lower middle-income countries.
3.4 Because of the rapid expansion of enrollment in 1960-84, enrollment increases at the primary level per se are an issue largely in the lowest-income countries. Table 10, page 25, lists the ten developing countries with the largest populations of out-of-school children in 1985 and their projected out-of-school populations for the year 2000, based on two scenarios of enrollment growth. In 1985, 31 percent of all the world's 6 to 1 1-year-olds and 61 percent of all out-of-school children that age lived in these 10 countries. To reduce the number of out-of- school children, enrollment growth in these countries would have to outstrip population growth. For many low-income countries, this is a tall order. On the other hand, the fact that
Education and Development: Evidencefor New Priorities 19 20 Educationand Development: Evidencefor New Priorities
Figure 2. Total Enrollment
400-
300 -
200-
100 -
O -1 l l l l I I I I I I 1960 1970 1980 1984
- Low Income Lower-Middle Income U--Upper-Middle Income High Income
India can reduce its out-of-school population to zero in the next 12 years if present economic growth rates are maintained, will have a significant impact on the problem at a world level.
3.5 In lower middle-income and many upper middle-income countries, the principal educa- tional problems are retention at the primary level and an appropriate expansion of places at the secondary and higher levels (see Figure 4, page 25, and Table 11, page 26). Although retention rates vary greatly among countries at every income level (for example, the high primary retention rates in Sri Lanka and Tanzania even at low per capita income levels), retention rates can be surprisingly low even in upper middle-income countries. Yet, the tendency is to attain universal primary education and high gross enrollment rates even in secondary education as the development level rises. Attention shifts to problems of retention at the secondary level. The most important educational issues in those developing countries that are newly industrialized and that are primarily oil-producers thus revolve around improv- ing the quality of primary, secondary and higher education rather than their expansion.
3.6 The enrollment and retention data, combined with rate of return estimates, suggest that countries at different levels of development have very different educational problems, and that appropriate policies therefore also vary substantially. In lower-income countries, the most appropriate emphasis is on delivering better quality education at the primary level and -- in many cases -- resolving the problem of high cost university (including the delivery of technical and scientific education at lower cost), and making rational choices of the most relevant type of secondary education. In higher-income countries, the emphasis has to be quite different, focusing much more on expanding and improving secondary education and producing high quality university graduates for new industries and services. Education and Development: Evidence for New Priorities 21
Table 9. Total Enrollment and Growth,1960-1984
Average Annual Growth Rate Total Enrollment (%) ('000) 1960- 1980- Income 1960 1970 1980 1984 1980 1984
Primary
Low Income Countries 145,411 191,527 277,024 270,797 (W) 3.1 0.1 (U) 7.1 3.2 (M) 6.6 3.0
Selected Countrieswith Low Enrollment Bhutan 3 9 30 44 12.2 10.0 Somalia 21 33 272 221 13.7 (5.1) Selected Countrieswith High Enrollment China 93,791 105,280 146,270 135,571 2.2 (1.9) India 34,994 57,045 73,873 81,097 3.8 2.4
Lower-MiddleIncome Countries 37,242 60,654 95,442 105,692 (W) 4.8 2.5 (U) 5.3 3.0 (MI) 4.9 3.1
SelectedCountries with Low Enrollment Botswana 36 83 172 210 8.1 5.1 Mauritania 11 32 91 107 11.1 4.1 Selected Countrieswith High Enrollment Indonesia 8,955 14,870 25,537 29,909 5.4 4.0 Nigeria 2,913 3,516 13,760 14,383 8.1 1.1
Upper-MiddleIncome Countries 42,838 63,408 83,283 88,385 (WV) 3A 1.5 (U) 2.5 1.0 (M) 2.0 0.8
SelectedCountries with Low Enrollment Panama 162 255 338 339 3.7 0.1 Uruguay 320 354 331 350 0.2 1.4 Selected Countrieswith High Enrollment Brazil 7,458 12,812 22,598 24,789 5.7 2.3 Mexico 4,885 9,248 14,666 15,219 5.7 0.9
High-Income Countries 69,693 68,377 65,962 63,385 (W) (0.3) (1.0) (U) 1.1 0.3 (M) (0.2) (0.6) SelectedCountries with Low Enrollment Kuwait 28 76 149 171 8.7 3.5 Trinidad& Tobago 179 226 167 168 (0.3) 0.1 Selected Countrieswith High Enrollment Japan 12,729 9,558 11,751 11,464 (0.4) (0.6) United States 29,965 28,700 27,448 26,839 (0.4) (0.6)
Note: (W) - WeightedMean (U) = UnweightedMean (M) Median 22 Education and Development: Evidence for New Priorities
Table 9 (cont.). Total Enrollment and Growth, 1960-1984
Average Annual Growth Rate TotalEnrollment (%) ('000) 1960- 1980- Income 1960 1970 1980 1984 1980 1984
Secondary
Low Income Countries 26,993.0 51,337.0 98,425.0 99,564.0 (W) 6.7 0.3 (U) 12.0 6.6 (M) 11.8 6.3
Selected Countries with Low Enrollment Bhutan 0.0 1.0 - 6.0 - - Somalia 3.0 25.0 44.0 63.0 14.4 9.4 Selected Countries with High Enrollment China 14,778.0 26,483.0 56,778.0 48,609.0 7.0 (3.8) India 10,125.0 20,114.0 31,597.0 37,869.0 5.9 4.6
Lower-Middle Income Countries 3,950.0 12,000.0 25,747.0 31,915.0 (W) 9.7 5.3 (U) 11.3 6.3 (M) 11.2 4.0
Selected Countries with Low Enrollment Botswana 1.0 5.0 21.0 31.0 16.4 10.2 Mauritania 1.0 4.0 22.0 - 16.7 - Selected Countries with High Enrollment Indonesia 727.0 2,460.0 5,722.0 7,446.0 10.9 6.8 Nigeria 167.0 357.0 2,346.0 3,561.0 14.1 11.0
Upper-Middle Income Countries 8,753.0 20,552.0 26,363.0 35,821.0 (WV) 6.5 3.1 (U) 6.3 4A
(M) 5.0 2.6 Selected Countries with Low Enrollment Panama 39.0 78.0 171.0 182.0 7.7 1.6 Uruguay 93.0 168.0 148.0 198.0 2.4 7.5 Selected Countries with High Enrollment Brazil 1,177.0 4,086.0 2,819.0 2,952.0 4.5 1.2 Mexico 512.0 1,584.0 4,742.0 6,064.0 11.8 6.3
High-Income Countries 28,443.0 49,948.0 54,966.0 57,588.0 (W) 2.5 1.4 (U) 5A 3.5 (M) 3.3 0.9
Selected Countries with Low Enrollment Kuwait 12.0 71.0 182.0 231.0 14.6 6.1 Trinidad & Tobago 24.0 53.0 89.0 92.0 6.8 0.8 Selected Countries with High Enrollment Japan 8,672.0 8,667.0 9,521.0 10,613.0 0.5 2.8 United States 9,600.0 19,910.0 14,556.0 13,779.0 2.1 (1.4)
Note: (W) = Weighted Mean (U) = Unweighted Mean (M) = Median Education and Development: Evidence for New Priorities 23
Table 9 (cont.). Total Enrollment and Growth, 1960-1984
Average Annual Growth Rate TotalEnrollment (%) ('000) 1960-1980- Income 1960 1970 1980 1984 1980 1984
Tertiary
Low Income Countries 2,125.2 3,332.7 7,119.3 8,485.2 (W) 6.2 4.5 (U) 10.2 11.7 (M%1)9.9 9.2
Selected Countrieswith Low Enrollment Bhutan - - 0.3 0.1 - (24.0) Somalia 0.1 1.0 - - - - Selected Countrieswith High Enrollment China 961.6 47.8 1,161.4 1,443.6 0.9 5.6 India 1,102.8 2,903.6 5,345.0 6,252.9 8.2 4.0
Lower-Middle Income Countries 657.6 1,911.5 4,434.8 6,645.2 (W) 9.2 8.7 (U) 13.6 9.4 (M) 12.7 5.4
Selected Countrieswith Low Enrollment Botswana - 0 0.9 1.8 - 18.9 Mauritania ------Selected Countrieswith High Enrollment Indonesia - 248.2 - 980.2 - - Nigeria - 15.6 150.1 181.6 - 4.9
Upper-Middle Income Countries 1,232.7 2,905.4 6,373.4 7,691.1 (W) 8.9 4.1 (U) 8.5 5.3 (M) 7.5 6A
Selected Countrieswith Low Enrollment Panama 4.0 8.9 40.4 52.2 12.3 6.6 Uruguay 15.3 - 36.3 63.7 4.4 15.1 SelectedCountries with High Enrollment Brazil 95.7 430.5 1,409.2 1,479.4 14.4 1.2 Mexico 78.6 247.6 897.7 1,071.7 12.9 4.5
High-IncomeCountries 5,882.6 14,079.0 20,768.4 22,114.7 (W) 6.5 1.6 (U) 8.7 6.5 (M) 7.4 4.1
SelectedCountries with Low Enrollment Kuwait - 2.7 13.6 21.9 - 12.6 Trinidad& Tobago 0.5 2.4 5.6 5.5 12.8 (0.4) SelectedCountries with High Enrollment Japan 789.8 1,819.3 2,412.1 2,403.4 5.7 (0.1) United States 3,582.7 8,498.1 12,096.9 12,467.7 6.3 0.8
Note: (W) = WeightedMean (U) = UnweightedMean (M) - Median 24 Education and Development: Evidence for New Priorities
Figure 3a. Primary School Enrollment Rates, 1960-1985
% of School-Aged Children Enrolled 120
1 0 0 ------=
80-
60 -
40-
20 - 0-7 1960 1965 1970 1975 1980 1985
- Low Income Lower-Middle Income ----- Upper-Middle Income High Income
Note: Figures more than 100% Indicate the number of overaged students enrolled at the primary level.
Figure 3b. Secondary School Enrollment Rates, 1960-1985
% of School-Aged Children Enrolled 120-
100-
80 -
60-
40 -
20 - 20 ol- I , 1960 1965 1970 1975 1980 1985
- Low Income Lower-Middle Income ----- Upper-Middle Income High Income
Note: Figures more than 100%Indicate the number of overaged students enrolled at the primary level. Education and Development: Evidence for New Piorities 25
Table 10. Out-of-School6 to 11-Year-Olds in Low-Income and Lower-MiddleIncome Countries (USSMillions)
Projectedfor 2000
Actual 2% Enrollment 5% Enrollment Category 1985 Growth Growth
Total Out-of-School 87 (21%) 129 (25%) 52 (10%)
Selectedcountries:
India 22.5 (25%) 12.6 (12%) 0.0 (0%) Pakistan 11.0 (70%) 19.0 (76%) 13.0 (52%) Bangladesh 6.7 (45%) 6.1 (35%) 0.0 (0%) Ethiopia 5.5 (81%) 9.7 (87%) 7.9 (71%) Nigeria 4.1 (26%) 14.6 (50%) 3.0 (10%) Afghanistan 2.7 (85%) 4.8 (89%) 4.4 (81%) Sudan 2.3 (68%) 4.4 (77%) 3.0 (53%) Egypt 2.3 (33%) 2.8 (30%) 0.0 (0%) Tanzania 2.0 (46%) 4.9 (64%) 2.5 (32%) Uganda 1.4 (49%) 2.9 (60%) 1.4 (29%)
Note: Numbers in parenthesesrefer to out-of-schoolchildren as a percentageof the populationof primaryschool-age children (6 to I1 years old).
Figure 4. RetentionRates by IncomeLevel
% Cohort Reaching 5th Grade 100 -
80-
60
40
20
0 - 1975 1980 1984
- Low Income - Lower-Middle Income Upper-Middle----- Income High Income 26 Education and Development: Evidence for New Priorities
Table 11. Retention Rates by Income Level
Percentage of Cohort Reaching Fifth Grade
Total Female
1975 1980 1984 1975 1980 1984
Low Income Countries (W) 40 44 38 37 42 41 (U) 55 57 54 52 55 52
Selected Countries with Low Rate Bangladesh - 23 23 - 23 25 Lao, People's Dem. Rep. - 22 20 - 23 19
Selected Countries with High Rate SriLanka 65 91 95 63 91 95 Tanzania 85 84 - 81 83 -
**China - - 64 - - **India 37 43 - 34 38 -
Lower-Middle Income Countries (W) 56 66 69 51 64 70 (U) 62 68 69 63 68 69 Selected Countries with Low Rate Guatemala 27 32 31 28 31 28 Nicaragua 27 27 23 - 30 26
Selected Countries with High Rate Jordan 95 103 112 94 103 113 Mauritius 97 98 96 97 99 96
Upper-Middle Income Countries (W) 56 60 56 81 73 72 (U) 76 78 81 79 81 84 Selected Countries with low rate Brazil 32 39 38 - - - Portugal 58 37 37 58 37 40 Selected Countries with High Rate Poland 103 99 100 - - - Iraq 91 96 130 85 92 123
High Income Countries (W) 94 99 100 95 96 101 (U) 88 92 98 89 90 97 Selected Countries with Low Rate Oman 51 80 90 90 65 84 Saudi Arabia 75 78 74 78 79 71
Selected Countries with High Rate Singapore 105 106 103 103 107 102 United Arab Emirates - 100 128 - 96 125
Note: (W) = Weighted Mean (U) = Unweighted Mean Education and Development: Evidence for New Priorities 27
Table 12. Public Recurrent Expenditures on Education as a Percentage of GNP
1970 1975 1980 1984
Low-IncomeCountries (U) 3.0 3.0 3.3 2.9
SelectedCountries with Low Expenditures Bangladesh - 1.1 1.5 1.8 Somalia 1.0 2.1 1.7 1.2
Selected Countrieswith High Expenditures Kenya 5.0 6.3 6.9 5.7 Tanzania 4.5 5.4 5.1 3.4
** China 1.3 1.8 2.5 2.3 ** India 2.8 2.8 3.0 2.4
Lower-MiddleIncome Countries (U) 3.5 4.2 4.6 4.1
SelectedCountries with Low Expenditures Paraguay 2.2 1.6 1.6 1.6 Philippines 2.6 1.9 1.6 1.3
Selected Countrieswith High Expenditures Botswana 5.2 8.5 7.1 8.4 Congo,People's Republic 5.9 8.1 6.9 -
Upper-MiddleIncome Countries (U) 4.2 4.3 4.5 3.6
Selected with Low Expenditures Brazil 2.9 3.0 3.4 1.0 Spain 2.1 1.8 2.3 1.9
SelectedCountries with High Expenditures Algeria 7.8 6.7 7.8 3.5 Ireland 5.0 6.2 6.6 6.2
High-IncomeCountries (U) 5.1 5.6 5.3 5.1
SelectedCountries with Low Expenditures Hong Kong 2.6 2.7 2.5 2.8 Oman - 1.6 2.1 3.6
SelectedCountries with High Expenditures Canada 8.9 7.8 7.5 7.4 Sweden 7.7 7.1 9.1 8.1
Note: (U) = UnweightedMean 28 Education and Development: Evidence for New Priorities
Table 13. Public Expenditures on Education as a Percentage of Total Government Expenditures
1970 1975 1980 1984
Low-Income Countries (W) 10.6 10.3 13.2 20.0 (U) 15.3 14.6 14.6 17.3 (M) 17.6 15.1 11.0 16.8
Selected Countries with Low Percentage Share China 2.9 4.2 6.1 - Pakistan 4.2 5.2 5.0 - Selected Countries with High Percentage Share Niger 17.7 18.7 22.9 - Rwanda 26.6 25.3 21.6 -
Lower-Middle Income Countries (W) 18.4 14.1 9.8 19.2 (U) 17.7 17.1 16.0 13.9 (M) 17.1 16.4 15.2 12.5
Selected Countries with Low Percentage Share Syrian Arab Republic 9.4 7.8 8.1 11.2 Jamaica 11.5 9.6 11.6 10.3 Selected Countries with High Percentage Share Costa Rica 31.8 31.1 22.2 18.9 Ecuador 23.2 25.9 33.3 -
Upper-Middle Income Countries (W) 11.1 10.8 14.7 2.3 (U) 16.3 13.1 16.0 11A (M) 15.2 11.9 14.9 9.8
Selected Countries with Low Percentage Share Hungary 6.9 4.2 5.2 6.4 Romania 8.0 6.4 6.7 - Selected Countries with High Percentage Share Algeria 31.6 23.0 24.3 - Yugoslavia 23.3 24.4 32.5 -
High Income Countries (W) 12.1 9.8 14.4 12.3 (U) 16.1 15.0 13.4 13.3 (M) 15.5 14.7 14.0 13.0
Selected Countries with Low Percentage Share Austria 8.1 8.5 8.0 8.0 Israel 8.1 7.6 7.3 - Selected Countries with high percentage share France 24.9 29.5 27.1 - Netherlands, The 29.4 23.7 23.1 -
Note: (W) = Weighted Mean (U) = Unweighted Mean (M) = Median Education and Development: Evidencefor New Priorities 29
Table 14. Public RecurrentExpenditures on Educationper Pupil
Expenditures Growth (US$) (%)
1975- 1980- 1975 1980 1984 1980 1984
Primary
Low Income Countries (W) 24.4 24.1 20.7 (0.2) (3.7) (U) 44.2 40.3 28.8 (1.8) (8.1) (M) 43.5 31.5 30.0 (6.3) (1.2) Selected Countrieswith Low Expenditures Bangladesh 4.0 6.0 9.0 8.4 10.7 Haiti 16.0 19.0 15.0 3.5 (5.7)
Selected Countrieswith High Expenditures Central AfricanRepublic 74.0 - 44.0 - - Mali - 54.0 59.0 - 2.2
** China ** India 23.0 23.0 - 0.0 0.0
Lower-MiddleIncome Countries (W) 73A 161.4 206.4 17.1 6.3 (U) 95.4 127.4 140.0 6.0 2.4 (M) 89.0 87.0 108.0 (0.5) 5.6 SelectedCountries with Low Expenditures Bolivia 72.0 82.0 51.0 2.6 (11.2) DominicanRepublic 35.0 33.0 51.0 (1.2) 11.5
Selected Countrieswith High Expenditures C6ted'Ivoire 147.0 160.0 - 1.7 - Turkey - 792.0 816.0 - 0.7
Upper-MiddleIncome Countries (W) 213.9 273.6 233.6 5.0 (3.9) (U) 299.3 334.8 340.7 2.3 OA (M) 206.0 229.0 300.0 2.1 7.0 Selected Countrieswith Low Expenditures Chile 86.0 181.0 241.0 16.0 7.4 Mexico 93.0 102.0 70.0 1.9 (9.0)
SelectedCountries with High Expenditures Iran, Islamic Republicof 288.0 659.0 315.0 18.0 (16.9) Ireland 648.0 592.0 879.0 (1.8) 10.4
High IncomeCountries (W) 2,406.6 1,248.2 1,468.6 (12.3) 4.1 (U) 1,601.2 1,550.8 1,986.9 (0.6) 6A (M) 1,099.0 1,168.0 1,445.0 1.2 5.5 Selected Countrieswith Low Expenditures Hong Kong 250.0 330.0 455.0 5.7 8.4 Israel 605.0 83.0 - (32.8) -
Selected Countrieswith HighExpenditures Kuwait 1,137.0 1,201.0 4,363.0 1.1 38.1 Norway 2,943.0 3,706.0 4,292.0 4.7 3.7
Note: (W) - WeightedMean (U) - UnweightedMean (M) = Median 30 Education and Development: Evidence for New Priorities
Table 14 (cont.). Public Recurrent Expenditures on Education per Pupil
Expenditures Growth (US$) (%)
1975- 1980- 1975 1980 1984 1980 1984
Secondary
Low Income Countries (W) 52.8 67A 91.9 5.0 8.1 (U) 284.1 176.6 103.5 (9.1) (12.5) (M) 191.0 156.0 111.5 (4.0) (8.1) Selected Countries with Low Expenditures Bangladesh - 12.0 15.0 - 5.7 Haiti - 42.0 21.0 - (15.9)
Selected Countries with High Expenditures Central African Republic 182.0 - 58.0 - Mali - 156.0 129.0 - (4.6)
** China 53.0 69.0 97.0 - ** India 42.0 - - -
Lower-Middle Income Countries (W) 187.5 200.3 184.0 1.3 (2.1) (U) 287.2 300.0 211.8 0.9 (8.3) (M) 230.0 232.5 173.5 0.2 (7.1) Selected Countries with Low Expenditures Bolivia 58.0 91.0 54.0 9.4 (12.2) Dominican Republic 66.0 63.0 69.0 (0.9) 2.3
Selected Countries with High Expenditures C6te D'Ivoire 814.0 801.0 - (0.3) - Turkey - - 1,585.0 - -
Upper-Middle Income Countries (W) 298.5 243.2 358.7 (4.0) 10.2 (U) 397.5 436.1 388.0 1.9 (2.9) (M~'1) 271.0 302.0 417.0 2.2 8.4 Selected Countries with Low Expenditures Chile 171.0 311.0 - 12.7 - Mexico 262.0 150.0 90.0 (10.6) (12.0)
Selected Countries with High Expenditures Iran, Islamic Republic of 615.0 - 567.0 - - Ireland 998.0 1,243.0 1,280.0 4.5 0.7
High Income Countries (W) 2,010.5 2,197.5 1,756.0 1.8 (5.5) (U) 2,073.0 2,221.4 2,320.6 1A 1.1 (M) 1,599.0 1,646.5 1,811.0 0.6 2.4 Selected Countries with Low Expenditures Hong Kong 235.0 403.0 603.0 11.4 10.6 Israel 1,483.0 224.0 - (31.5) -
Selected Countries with High Expenditures Kuwait 1,569.0 1,398.0 1,877.0 (2.3) 7.6 Norway 1,779.0 2,033.0 2,051.0 2.7 0.2
Note: (W) = Weighted Mean (U) = Unweighted Mean (M) = Median Education and Development: Evidencefor New Priorities 31
Table 14 (cont.). Public RecurrentExpenditures on Educationper Pupil
Expenditures Growth (US$) (%)
1975- 1980- 1975 1980 1984 1980 1984
Tertiary
Low IncomeCountries (W) 212.1 825.9 677.1 31.2 (4.8) (U) 2,704.4 2,071.1 1,167.0 (5.2)(13.4) (M) 2,298.0 1,834.0 1,067.0 (4.4) (12.7) Selected Countrieswith Low Expenditures Bangladesh - 106.0 78.0 - (7.4) Haiti 494.0 419.0 278.0 (3.2) (9.7)
Selected Countrieswith High Expenditures 4,278.0 - 1,745.0 - CentralAfrican Republic 2,298.0 6,196.0 1,287.0 21.9 (32.5) Mali
** China 837.0 857.0 845.0 0.5 (0.4) -* India 99.0 - - 0.0 0.0
Lower-Middle Income Countries (W) 858.7 1,110.9 3,124.9 5.3 29.5 (U) 2,686.8 2,025.4 2,070.7 (5.5) 0.6 (M) 1,189.0 1,050.0 1,347.0 (2.5) 6.4 Selected Countrieswith Low Expenditures Bolivia 310.0 - - - - DominicanRepublic
SelectedCountries with High Expenditures Cote D'Ivoire 6,969.0 3,287.0 - (14.0) Turkey - 11,787.0 6,453.0 - (14.0)
Upper-Middle Income Countries (W) 1,924.1 1,280.5 918A (7.8) (8.0) (U) 2,852.1 2,029.0 1,617.3 (6.6) (5.5) () 880.5 1,053.0 768.0 3.6 (7.6) SelectedCountries with Low Expenditures Chile 959.0 2,119.0 1,167.0 17.2 (13.9) Mexico 555.0 1,113.0 931.0 14.9 (4.4)
SelectedCountries with High Expenditures Iran, Islamic Republicof 19,246.0 - 5,232.0 - Ireland 2,802.0 3,063.0 2,731.0 1.8 (2.8)
High Income Countries (W) 4,018.9 3,243.1 2,494.4 (4.2) (6.4) (U) 4,392.9 4,226.6 3,834.9 (0.8) (2.4) (M) 3,831.5 3,446.0 3,460.0 (2.1) 0.1 Selected Countrieswith Low Expenditures Hong Kong 1,533.0 3,411.0 2,539.0 17.3 (7.1) Israel - 392.0 407.0 - 0.9
Selected Countrieswith High Expenditures Kuwait 9,365.0 7,345.0 8,550.0 (4.7) 3.9 Norway 4,696.0 5,189.0 4,765.0 2.0 (2.1)
Note: (W) = WeightedMean (U) = UnweightedMean (M) - Median 32 Education and Development: Evidence for New Priorities
Table 15. Public Recurrent Expenditures on Education per Pupil as a Percentage of GNP Per Capita
Primary Secondary Tertiary
1975 1980 1984 1975 1980 1984 1975 1980 1984
Low-Income Countries (W) 16.0 15.6 12.5 102.7 68.7 37.2 9.9 8.1 6.0 (U) 17.4 15.8 14.9 107.9 71.9 43A 10.6 9.7 6.9 (M) 13.5 13.5 15.0 75.5 60.0 29.0 9.7 6.8 5.8
Selected Countries with Low Expenditures Bangladesh 4.0 5.0 7.0 - 10.0 12.0 - 0.9 0.6 Haiti 6.0 6.0 5.0 - 12.0 7.0 1.7 1.2 0.9
Selected Countries with High Expenditures Ethiopia 35.0 19.0 23.0 - - - - 13.0 14.0 Mali - 32.0 40.0 - 92.0 87.0 15.8 36.7 8.7
A* China - - - 28.0 30.0 32.0 4.5 3.8 2.7 A* India 11.0 10.0 - 19.0 - - 0.5 - -
Lower-Middle Income Countries (W) 11.0 14.0 13.6 31.3 32A 32.8 3.2 2.0 1.7 (U) 13.0 14.7 14.0 37.4 39.9 35.6 3A 2.2 1.8 (M) 10.0 12.0 11.0 19.0 20.5 21.0 1.1 0.9 1.2
Selected Countries with Low Expenditures DominicanRepublic 4.0 3.0 5.0 7.0 6.0 7.0 - - - Syrian Arab Republic 5.0 5.0 7.0 10.0 10.0 9.0 0.6 0.5 0.7
Selected Countries with High Expenditures C6te d'Ivoire 21.0 21.0 - 115.0 104.0 - 9.9 4.3 Morocco 20.0 16.0 19.0 74.0 59.0 48.0 2.3 1.6 1.8
Upper-Middle Income Countries (W) 11.2 13.2 16.0 14.3 15.5 17.2 1.1 0.7 0.7 (U) 12.1 12.9 15.6 14.1 16.0 16.1 0.8 0.8 0.6 (Nt) 7.0 10.0 14.0 15.0 13.0 12.5 0.4 0.4 0.5
Selected Countries with Low Expenditures Greece 6.0 7.0 - 7.0 8.0 - 0.3 0.3 Mexico 6.0 5.0 4.0 16.0 8.0 5.0 0.3 0.6 0.5
Selected Countries with High Expenditures Iran, Islamic Rep. of 7.0 21.0 - 14.0 - - 4.4 - Ireland 15.0 12.0 18.0 23.0 25.0 26.0 0.6 0.6 0.6
Note: (W) = Weighted Mean (U) = Unweighted Mean (M) = Median. Education and Development: Evidencefor New Priorities 33
Table 15 (cont.). Public Recurrent Expenditures on Education per Pupil as a Percentage of GNP Per Capita
Primary Secondary Tertiary
1975 1980 1984 1975 1980 1984 1975 1980 1984
High-Income Countries (W) 19.6 17.2 19.8 24.8 23.3 24.4 0.5 0.4 0.4 (U) 18A 16.3 17.9 23.2 21.8 22.9 0.5 OA OA (M) 14.5 13.5 15.5 20.0 16.5 21.0 0.5 0.4 0.4
Selected Countries with Low Expenditures Israel 12.0 2.0 - 29.0 4.0 - - 0.1 0.1 Singapore 7.0 7.0 8.0 11.0 14.0 11.0 0.4 0.4 0.6
SelectedCountries with High Expenditures Norway 29.0 30.0 32.0 17.0 16.0 15.0 0.5 0.4 0.4 Sweden 29.0 44.0 44.0 14.0 15.0 16.0 0.4 0.3 0.3
Note: (W) = WeightedMean (U) = UnweightedMean (M) Median.
3.7 Comparing rate of return estimates with enrollment expansion also suggests that many countries are investing in education consistently with the way that economic payoff data suggest they should be. Other countries are not. Generally, these countries are overinvesting in higher education and underinvesting in primary education -- in many cases, underinvesting particularly in girls' primary education.
The Educational Spending Crisis
3.8 There are also well-developed data on educational spending, by country and over time. Table 12, page 27, shows that slower economic growth in the 1980s has been accompa- nied by cuts in the percentage of GNP going to public education -- this, after increases in the 1970s. Table 13, page 28, suggests (looking at the unweighted means) that all but the low- income countries have accomplished this cut in spending on education by cutting the percent- age of public budgets going to education; that is, by shifting resources to other public spending objectives.
3.9 The net result of these policies is shown in Tables 14, page 29, and 15, page 32 - the growth of spending-per-pupil and the amount spent per pupil at different levels of education as a percentage of GNP per capita. Again, focusing on the unweighted means in Table 14, the results show that in low-income countries, where spending-per-pupil in primary schools is very low, this spending declined in 1975-84, especially in 1980-84. At the secondary level, where spending-per-pupil was the same in 1975, on average, as in lower middle-income countries, cuts were even more rapid, although all these cuts and particularly the cuts in higher education could be rationalized in terms of what spending-per-pupil "should" be in terms of income per capita (Table 15). The "right" amount of spending-per-pupil is a crucial issue in developing educational quality criteria. But in general, if the U.S./European model of school- ing is to be duplicated in low-income countries, it is likely that per-pupil spending as a ratio of income per capita will be higher than in higher-income countries, primarily because of the greater scarcity of teacher skills. 34 Education and Development: Evidencefor New Priorities
3.10 It is clear from these data that the 1970s and especially the 1980s have been periods of declining growth of real public spending on education, particularly per-pupil-spending. Between 1975 and 1980, for example, this growth rate was lower than the growth of national income for more than one-third of a sample of 55 countries (World Bank, 1986).
3.11 The trend reflects two mutually reinforcing factors: (a) the decline in many countries of overall public budgets in real terms in the wake of the two major world recessions of 1974- 75 and 1980-83 combined with severe foreign debt crises in Latin America, Sub-Saharan Africa, and some countries in Asia and -- in the Middle East -- lower oil prices (Haddad and Demsky, 1987); and (b) the large proportion of government budgets devoted to education, especially in Sub-Saharan Africa and Latin America. With tight finances, intersectoral compe- tition for resources seems to have put pressure on social spending, particularly education. This has resulted in a declining budget share for public education in most of the world's regions. Although there are some important exceptions to this trend (China, the Republic of Korea, and Taiwan), many countries have experienced much larger declines than the average figures suggest. In some countries, furthermore, declines in the percentage of the public budget going to education have been accompanied by increases in the proportion spent on the military (Camoy, 1986).
3.12 Statistics on the private flow of funds to education are scarce, but existing data show that as a share of total national educational expenditures, private spending has also declined in most developing countries (World Bank, 1986).
3.13 The decline in growth of educational spending goes counter to two other trends: continued rapid growth of the school-age population in many of the world's lowest-income countries and an increase in average cost-per-pupil as the average level of education attended increases from low-cost primary to higher-cost secondary and university. Most Sub-Saharan African and particularly Latin American countries have attempted to deal with this impasse by reducing real spending-per-pupil at all levels, especially in Latin America at the tertiary level (see Heller and Cheasty, 1984, and Table 15, page 32). Others have not kept up with school- age population growth, increasing the absolute number of primary school-age children not in school.
3.14 Many Asian countries, however, have increased per-pupil spending in the 1980s (although not as rapidly as in the 1970s) even as the percentage of their public spending on education has continued to decline. This suggests that in higher economic growth regions with low rates of population increase, the problems of educational finance have rather different dimensions than in the lower economic growth/higher population growth regions Sub-Saharan Africa and Latin America. And in many Latin American countries, relatively high primary school survival rates and secondary school enrollment rates mean that the educational crisis is largely one of expanding the secondary and tertiary levels rather than the primary level (Brazil is a notable exception among the larger countries). It also suggests that the economic develop- ment gap between the more rapidly developing countries in Asia and the lower-income coun- tries in Sub-Saharan Africa and Latin America is bound to increase as education expands in the faster-growing countries and falls behind in the stagnant ones. Even the larger, higher- income countries in Latin America stand to hurt their future technological modernization as their educational systems fail to keep pace with development requirements.
3.15 These data also indicate that although the cost of providing all children access to good education is great, the goal is within reach. If the economic growth rate in the low-income countries (excluding China and India, whose universal primary school enrollment should not be a financial problem) is 3.2 percent, and in the low middle-income countries, 3.0 percent, between 1985 and 2000, recurrent expenditures for primary education would have to reach 2.4 and 1.9 percent of GNP, respectively, in order to achieve 100 percent enrollment. In Education and Development: Evidence for New Priorities 35
Sub-Saharan Africa, countries already spend a high percentage of their public budget on edu- cation -- they need policies to more efficiently allocate resources and diversify their resource base, as well as new, highly effective approaches to teaching and learning. In South Asia, the problem is mainly underfinancing of education, but countries such as Bangladesh also need new approaches to delivering education.
4 Lessons from World Bank and Other Donor Experience with Assistance to Education and Training
4.1 The World Bank has been investing in education for 25 years. It has made loans for over 350 projects in 92 countries. Operations Evaluation Department (OED) project comple- tion reports are available for 161 projects, and audits of these completed projects are also available. In addition, the Bank has done sector performance analyses and summaries of experiences in education. Therefore, a vast amount of Bank experience in educational invest- ment has been extensively chronicled and assessed.
4.2 Other donors have also invested heavily in developing countries' education. These include: (i) the regional development banks -- Asian, African, and Inter-American; (ii) the bilateral agencies -- USAID, CIDA, SIDA, ODA, NORAD, Canadian IDRC, DANIDA, and French Cooperation; (iii) the international agencies -- UNESCO, UNICEF, and ILO; and (iv) the foundations -- primarily Ford and Rockefeller. Their experiences have also been chronicled and many evaluated.
Total Education Sector Lending by Multilateral and Bilateral Agencies
4.3 The World Bank plays a singularly important role in international lending for educa- tion. Since the 1970s it has been the largest single provider of external funding for educational development, providing approximately 15 percent of all official external aid to education (Table 16). Since bilateral aid is largely for technical assistance, the Bank is by far the larger lender for capital investments. In many countries the Bank is the major source of educational policy advice, and other agencies increasingly follow the Bank's lead in such policy and lending. Therefore, its experiences and the policy implications of those experiences carry particularly significant weight in how educational development and lending proceeds world- wide. With more than US$4 billion flowing to developing countries annually for education and training, the World Bank will make an important impact on educational change -- hence economic development -- in the coming decade.
History of Bank Investments in Education and Training
4.4 The World Bank loaned US$11.2 billion dollars for education in 1962-87 through 355 education projects. Although the absolute amount of education and training loans has varied from year to year, in relative terms, they have stayed at about six percent of total annual loans (Table 16), somewhat less than other multilateral agencies and much less relatively than bilateral lending agencies.
Education and Development: Evidence for New Priorities 37 38 Education and Development: Evidence for New Priorities
Table 16. Comparative Flow of Education Aid, 1980486 (USSMinions)
BilateralAidfrom Other MemberCountries Multilateral of the DAC WorldBank Agencies of the OECD b Total
World Bank % of % of Aid % of Aid % of Aid % of Total Educ. Total to Total to Total to Total Educ. Year Lending Lending Educ. Aid Educ. Aid Educ. Aid Aid
1980 440.1 3.8 256.7 5.8 3,394.8 13.9 4,091.6 10.2 16.8
1981 747.9 6.1 296.4 5.9 2,595.9 11.4 3,640.2 9.1 20.6
1982 526.4 4.0 468.1 8.7 2,542.6 11.1 3,537.1 8.6 14.9
1983 547.9 3.8 498.9 8.2 2,755.7 11.7 3,802.5 8.6 14.4
1984 701.9 4.5 331.3 4.8 3,213.6 12.2 4,246.8 8.7 16.5
1985 936.8 6.5 338.2 5.4 4,997.7 13.0 4,125.5 9.7 14.9
1986 839.5 5.1 453.8 6.8 2,858.9 10.9 4,702.9 9.6 20.2
. Includes African DevelopmentBank, Asian DevelopmentBank, Inter-AmericanDevelopment Bank, Islamic DevelopmentBank, UNICEFand UNESCO. b Includes loans, grants, etc. (excludescontributions to multilateralorganizations).
Table 17. Distributionof Lending for Educationand Trainingby Region (USSMillions)
Period Africa Asia LAC EMENA Total
Total 2,466 4,235 1,529 3,011 11,241
FY63-68 206 89 61 123 479 FY69-73 577 479 233 433 1,722 FY74-78 537 516 421 742 2,216 FY79-83 538 1,381 367 709 2,995 FY84-88 561 1,770 447 1,004 3,782 Education and Development: Evidence for New Priorities 39
Table 18. Distributionof Investmentsby Type of Curricula and Level of Education
Type FY63-76 FY77-86
Total 100% 100%
General Education 43% 53% Primary 6% 22% Secondary 20% 10% NonformalLiteracy 1% - Post-Secondary 4% 14% TeacherTraining 11% 6%
VocationalEducation 51% 44% Secondary 23% 6% Post-Secondary 16% 24% NonformalSkill Training 11% 13% TeacherTraining 1% 1%
Non-Allocated 7% 3%
Table 19. Pattern of Education Project Expenditures
Type FY79-81 FY84-86
Total 100% 100%
CivilWorks 55% 44% Equipment& Furniture 29% 31% TechnicalAssistance 7% 10% Other Expenditures 9% 15%
Table 20. Education Subsector Reviews
FY84-85 Relation of sector work and completion reporting to education projects' preparation
FY85 Effectiveness of varied training modes in provision of project-related train- ing components
FY86-87 Performance review of free-standing vocational training projects in both education and non-education sectors
FY88 Review of experience with policy-based lending in education projects 40 Education and Development: Evidence for New Priorities
Table 21. Reviews of Bank Experiencein the EducationSector
Primary Education Examinationof Bank performance in provision of primary education through68 projects,at a total project cost of US$1.4billion.
SecondaryEducation Analysis of Bank experiencewith specializedsecondary school curricula supportedin 79 educationprojects throughFY63-79 that attemptedto "vo- cationalize"part of a generalsecondary school curricula.
UniversityEducation Review of Bank experiencewith lending for universitylevel education in 120 educationprojects through FY63-88 (to be completedDecember 1988).
Adult Literacy Evaluationof policy and experiencein 92 Bank educationprojects during FY63-85that taught adult literacy and basic skill trainingthrough project componentsoutside of the formal schoolsystem.
VocationalEducation Industry: Analysis of the performanceof Bank investmentsin vocational training for industry through76 projectsin FY63-87covering US$4.7 bil- lion project costs.
Commerce: Evaluationof Bank experiencewith 43 investmentsin com- merce training(to be completedJanuary 1989).
DistanceEducation Reviewof Bankexperience in 32 distanceeducation components (i.e. radio, television,correspondence courses) during FY63-85.
Textbooks Reviewof Bank experiencethrough 48 project componentsin FY63-83for the preparation,provision and distributionof learningmaterials and teacher guides.
TeacherTraining Study of the effectivenessof 149 teacher training componentsfor primary and secondaryteachers in Bank education projects, covering 9 percent of educationlending in FY63-84.
SectorManagement Analysis of education sector managementcomponents through 17 educa- tion projects in 12 countries.
Monitoring& Evaluation Examinationof three case studies of Bank educationprojects with success- ful monitoringand evaluationcomponents.
Sector Loans Evaluationof seven educationsector loansto identifyprocedural issues for future preparationof sector loans and sectoraladjustment projects.
EducationalChange General Experience: Examinationof the performance of Bank project componentsaimed at educationalquality improvementand change,through FY63-84,totalling US$6.4billion of total project costs (60% of all educa- tion projectscosts).
Teaching: In-depthreview of 21 educationproject componentsfor teacher trainingdesigned to support the implementationof project componentsfor educationalquality improvement.
Textbooks: In-depth review of lt educationproject componentsfor text- book productionand/or provision designedto support the implementation of project componentsfor educationalquality improvements. Education and Development: Evidence for New Priorities 41
4.5 The focus of the Bank's education lending has shifted over time across three dimen- sions: regionally, by level of education, and by type of project components. The Bank has moved from an early emphasis on Sub-Saharan Africa to a much higher percentage of lending to Asia and the Middle East (Table 17). The Bank has also shifted from a heavy emphasis on general and vocational secondary education in the FY63-76 period to much greater focus on primary and post-secondary education (general and vocational) in the FY77-88 period (Table 18). This was consistent with the objectives set out in the 1980 Education Sector Policy Paper, emphasizing investments in basic education in low-income countries, and secondary and higher education in those middle-income countries where basic education has been estab- lished. There was also a much more gradual change from lending for buildings to technical assistance and other expenditures (Table 19, page 39).
4.6 Investments by the Bank in education and training are carried out through two main channels: (1) Education projects, which lend directly for general and technical education at primary, secondary, and tertiary levels, and vocational education and training for specific occupational fields; and (2) Project-related training (PRT), i.e., training components in non- education projects (indirect lending for education), aimed at ensuring that project objectives are not constrained by lack of adequately skilled manpower.
Education and Training DepartmenVDivision Reviews: Reviews of Education and Training Operations
4.7 Annual reviews of the Bank's operations in education lending and project-related training components (which averages US$600 million or about six percent of overall Bank annual lending) have been prepared by the human resources sector staff in the PPR complex (and by their pre-Reorganization forerunners -- Operations Policy Staff) each year since FY77. Changes in regional lending patterns are reviewed, and any fluctuations are then examined within the context of three-year or five-year lending patterns.
4.8 Project costs are also compiled by: (1) level of education (primary, secondary, university, and vocational training); (2) curricula (basic/general and technicaVvocational); and (3) category of expenditure (civil works, equipment & furniture, technical assistance). Again, fluctuations are reviewed within an annual and a three-year or five-year context.
Table 22. OED Project Completion/AuditReports in the Education Sector
Countrieswith More than One CompletionWAuditReport
TotalNo. No. of Reports of CompletiorVAudit Region Reports 2 3 4
Africa 64 15 4 3
Asia 29 2 - 5 a
EMENA 35 6 2 3
LAC 33 11 3 -
Total 161 34 9 11
* Includes Indonesiaand the Philippines,with five and six reports, respectively. 42 Education and Development: Evidence for New Priorities
4.9 For the past five years these annual reviews have also been used as an opportunity to concentrate on subsector issues of interest to operational staff:
Education and Training DepartmenVDivision Reviews: Reviews of Sectoral Performance
4.10 In addition to annual reviews of lending, the Bank has also conducted reviews of its experience in important subsectors of education lending, as shown in Table 21, page 40.
Operations Evaluation Department Reviews: Reviews of Education Project Performance
4.11 OED has conducted project performance evaluations for 161 completed education projects, in the form of Project Completion Reports and Project Performance Audit Reports. In addition, OED has prepared Impact Evaluation Reports on education projects in Colombia, the Philippines and Thailand. These performance reviews cut across the many levels and types of projects in which the Bank has invested. A particular benefit of these reviews lies in the 11 countries where the Bank has had "lessons leamed" from a series of at least four completed projects (Table 22, page 41).
Operations Evaluation Department Reviews: Reviews of Sectoral Performance
4.12 In addition to reviewing discrete education projects, OED has conducted reviews of sectoral operations on: (1) the formal education sector (1978); (2) the project-related training sector (1982); and (3) the impact of 15 years of Bank education investments in Korea (1985).
Education Sector Performance Review by Other Donor Agencies
4.13 Complementary to the Bank's internal evaluations of its project and sectoral perform- ance in education, many other agencies have a long history of involvement in the education and training sector. In particular, two other UN agencies -- UNESCO and UNICEF, the bilateral agencies -- the United States Agency for Intemational Development (USAID), the Swedish International Development Authority (SIDA), the Canadian International Develop- ment Agency (CIDA), and the Canadian International Development Research Centre (IDRC), and independent agencies such as the Rockefeller and Ford Foundations have a wealth of experience. Collaboration with these agencies is a common experience throughout the Bank's activities in education lending, and some of their internal evaluation resources available to the Bank are shown in Table 23. Education and Development: Evidence for New Priorities 43
Table 23. Evaluations of Education and Training Activities Available from other Agencies
Number of Years Involvedin Available Education Evaluation Agency and Training Reports
UNESCO 43 75
IDRC 11 110
SIDA 23 160
ROCKEFELLER 13 130
UNICEF 25 105
USAID 27 90
5 Policy Issues and Directions
5.1 An extensive body of analyses is available assessing the impact of various interven- tions on the effectiveness and efficiency of education and the learning process. These analyses are divided into seven topics: (i) skill formation (vocational education and training); (ii) the quality and efficiency of education; (iii) technology in education; (iv) sector management; (v) science education; (vi) higher education and technology transfer; and (vii) educational financial reforms.
Vocational and Academic Secondary Education
5.2 When educational planners in developing countries consider investing in education for economic development, many think of vocational education and training, especially at the secondary level (Bacchus, 1988). It is such directly job skills-related education that many planners believe to be most connected to increasing economic output. Vocational education's popularity among policymakers also stems in part from its social function. It tends to be substituted for general education for students who do not succeed academically. Policymakers want to prepare these less academically able students for some sort of practical work and to reduce pressure on higher education by making vocational education terminal. It is precisely for this reason that there has never been much enthusiasm among students or their parents for such education, except as a second-best way to avoid unemployment (Foster, 1966).
5.3 There are now a large number of studies -- many of them carried out for the World Bank (Picciotto, 1965; Fuller, 1970; Arriagazzi, 1972; Borus, 1977; Godfrey, 1977; Castro, 1979; Levine, 1979; Puryear, 1979; Psacharopoulos, 1982; Cohen, 1983; Ziderman, 1988; Grootaert, 1988) -- which challenge the notion that skill training in vocational schools is the best educational investment strategy for economic development, or even the most cost- effective way to impart those skills (see Table 24). They recommend alternative strategies. Metcalf (1985) summarizes this research. The studies show, he argues, that although there is economic justification for public intervention in the training effort (as evidenced by reasonably high rates of return to vocational training), training carried out in industrial institutes and vocational secondary schools appears to be less cost-effective than more informal, firm-based training; short-courses appear to have a bigger payoff than longer courses of training; and the payoff to quasi-institutional vocational training may be higher for those who have completed primary school than for those who have completed secondary. Grootaert's analysis of voca- tional education in the C6te d'Ivoire (1988) confirms the low return to all levels of formal vocational education, but shows that returns to higher secondary vocational education are not as low as those to post-primary vocational education.
Education and Development: Evidence for New Priorities 45 46 Education and Development: Evidence for New Priorities
Table 24. Vocational-Technical Education and Training versus Academic Education: Selected Empirical Studies in Developing Countries
Study Data Results
Foster (1966) Students in Ghana Classic study which argues that all education is vocational but that "voca- tional" education (VTE) and training is considered second-rate because it leads to lower status occupations than academic track. This is known as the 'vocational education fallacy."
Metcalf (1985) Review of studies Rate of return to vocational training is in a number of different high enough to justify investment. countries Shorter courses have a higher payoff. Inforrnal firm-based training is more cost-effective than vocational secon- dary schools. In South America, voca- tional training for primary school completers has higher payoff than to secondary school completers. VTE in industry-linked institutions has higher payoff than in non-affiliated institutions.
Fuller (1970) Survey of workers Productivity of in-school vocational in two electrical trained workers is 9% lower than machinery plants in-firm trained workers and costs of in- in Bangalore, India school training are higher.
Godfrey (1977) 400+ exam candidates Graduates with school vocational training in Kenya, 1973 are 14-25% less likely to pass government craft tests than those with no such training.
Psacharopoulos Six firmnsin Lima, Short SENATI courses gave high returns, (1988) Peru in 1982 whereas two-year SENATI courses had low returns.
Castro (1979) Brazil--Sao Paulo & Social rates of return of SENAI own-firmn Rio manufacturing training were higher for those workers sector, large firms, 1970 with completed secondary education than those with junior high. Rates rather high.
Puryear (1979) Bogota, Colombia Three-year SENA graduates earn, over a 1965-67 SENA graduates, SENA apprenticeship sample as a whole, sampled in 1972 48% more than equivalent non-SENA graduates, but this SENA effect is smaller for those with more than six years of schooling.
Psacharapoulos Follow-up survey There is no labor advantage to graduates and Loxley (1985) of graduates from from vocational courses, either in terms diversified and of success in finding employment or in non-diversified secondary pay levels when employed either in in Colombia or Tanzania Colombia or Tanzania. Costs of programs are also similar. Education and Development: Evidence for New Priorities 47
Table 24 (cont.). Vocational-TechnicalEducation and Training versus Academic Education: Selected Empirical Studies in DevelopingCountries
Study Data Resuls
Hinchliffe(1983) Tanzania Totalannual unit recurrentcosts are 19% higher in agriculturalbiased schools, 13% higher in technicalbiased schools, and 9% higher in commercebiased schools comparedwith academicschools.
Cummings,et al. (1985) Kenya Staffingcosts are twice and and capital costs are five times for industrialeduca- tion subjectsas for those of classroom subjects.
Tibi (1986) Thailand Recurrentcosts of agriculturalcolleges were 98% higher and three kinds of technicalcolleges were 54% higher than in professionalcolleges.
Komenan (1987) Ivory Coast 1984 Technicaleducation has higher payoff labor force survey than general educationat every level of schooling,but costs of technicaleducation are muchhigher (2.5 times higher at secondarylevel).
Grootaert(1988) Ivory Coast,Living Social rates of return are low to VTE, StandardsSurvey, 1985 but higher to post-secondarythan to post- primary VTE, and higher than to appren- ticeship training.Private rates of return are much higher because of large public costs. Rates are also higherto those outside of Abidjan.
Moock and Male urban sub- Monetary returns are generallysimilar to Bellew (1988) sampleof Peru VTE and academicstream graduates, Living Standards exceptfor self-employedoutside Lima. Survey, 1985/86 Unit costs are also similar for VTE and academicstreams.
Chung (1987) Hong Kong census, Retums to VTE are higher than to 1976 and 1981 general education, but significantonly for the rapidly-growingelectrical and commercialsectors.
Min and Tsang (1987) Survey of workers Productivityof workerswith VTE 7% in Beijing General higher than those with general secondary Auto IndustryCompany education.
Ziderman(1988) Israel, 1983 census Vocationalsecondary schooling more cost-effectivethan general educationfor those who do not go on to post-secondary education,especially for those who work in occupationsrelated to courseof study. 48 Education and Development: Evidence for New Priorities
Table 24 (cont.). Vocational-TechnicalEducation and Trainingversus AcademicEducation: Selected EmpiricalStudies in DevelopingCountries
Study Data Results
Lee, C. (1985) South Korea In-plantvocational training is more cost- secondarygraduates effectivethan trainingin vocational schools.
Chin-Aleong(1988) Trinidad& Tobago Specializedcraft students foundjobs labor force survey more quickly and earned better salaries than did academicstudents or those with pretechniciancourses.
Schiefelbein& Sample of eighth Trackingstudents into vocational Farrell (1982) grade Chileanstudents curriculawhere academicachievement is not emphasizedwill lower student achievement.
Noah and Middleton Secondarydata from China is attemptingto reach a 50-50 (1988) two provincesin China: generalto vocationaleducation Lingoningand Hubeii enrollmentmix by 1990. But they concludethat in order to meet the demandsof economy,China needs to shift away from apprenticeship-VTEto in- school VTE.
5.4 Recent research by Psacharopoulos and Loxley (1985) on Colombia and Tanzania, Lauglo and Narman (1988) in Kenya and Chin-Aleong (1988) in Trinidad and Tobago suggests that the cost-effectiveness of introducing pre-vocational subjects in traditional secon- dary schools (diversified secondary education) is also low if their goal is to help school-leavers find a source of livelihood under difficult labor market conditions. There may be other reasons for diversifying secondary schools -- such as giving students some experience in manual work or attempting to provide greater equity in access to academic secondary educa- tion, but pre-vocational courses may be an expensive way to achieve these goals.
5.5 There is some evidence that schooling is complementary to in-firm and project train- ing. Fuller found in his Bangalore, India study (1970) that extra schooling seems to be an important prerequisite for on-the-job learning. In a more approximate estimation, Mingat (1984) sampled 52 worldwide agricultural projects supported by the World Bank in the early 1980s, and found that the returns to project-related training are larger, the higher the adult literacy rate in the country.
5.6 More than twenty years of studying vocational education therefore raises serious questions about the economic value of investing in expensive vocational schooling, especially where such schooling is not directly connected to an employment situation (as in some of the Latin American systems such as SENA (Colombia) and SENAI (Brazil)). Vocational educa- tion is much more expensive than academic, and, if unconnected to an employer or group of employers, does not appear to give graduates any advantage in finding work or earning higher wages. Education and Development: Evidence for New Priorities 49
5.7 However, under certain conditions, vocational education may have a high payoff. In-firm training or training in institutions with an employment connection (SENA and SENAI, for example; see also Min and Tsang, 1987, for the higher productivity of workers with vocational education in China) may yield a reasonably high benefit-cost ratio. Recent research in Hong Kong (Chung, 1987) and an extensive review of World Bank investment in vocational education and training (Middleton and Demsky, 1988) also suggest that investment in voca- tional education in those skills relevant to rapidly growing industries and, more generally, in industrially dynamic economies, have a higher payoff than to academic education. Chung shows that workers who graduated from vocational education institutions that prepared them for careers in such rapidly growing industries were more likely to work in the jobs for which they were trained and eamed higher wages than their counterparts with academic education.
5.8 All this suggests a more selective approach to investing in vocational education and training, focusing much more on in-firn and firm-connected or industry-connected programs, and on those related to rapidly growing sectors. In the middle-income countries, training investments should support the introduction of new technologies and continuous industrial restructuring -- which means upgrading the general knowledge and specific skills of the labor force. General education would usually take place off-the-job, but much of the skill training can be industry-based. For this purpose, technologies have been developed in recent years using advances in the electronic media. Few developing countries are adequately exploiting the potential of these technologies.
5.9 Low-income countries -- with weak enterprises and stagnant demand for skills -- require a different training strategy. Pre-employment training is more important, since enter- prises themselves have little training capacity, and this training should be more generic, focus- ing on general academic preparation in science, mathematics, and language (Heyneman, 1987), which makes workers more trainable, and on self-employment and entrepreneurship (Komenan, 1987).
5.10 There are also still a number of unanswered questions, such as the relative adaptabil- ity of academically and vocationally-trained workers to work situations involving rapid tech- nological change. This is particularly important when we consider that the organization of industrial production is undergoing significant and rapid change and that many developing countries are seeking high technology transfer. The evidence suggesting that academic school- ing is complementary to on-the-job learning (Fuller, 1970) indicates that those workers with more academic skills may be more adaptable and easier to retrain. But more research is needed to confirm such results.
The Quality and Efficiency of Education
5.11 Students in low-income countries are not only getting less years of education, they are learning less in each of those years than students in higher-income countries: mathematics and science scores are lower in low-income and most middle-income countries than in the NICs and industrialized countries (Heyneman and Loxley, 1983; Table 25, page 51). Further, the knowledge gap may be growing: measured in terms of spending-per-pupil and the ratio of pupils to teachers, quality of education has declined in the lowest-income countries and im- proved in the middle-income countries; and developing countries with higher enrollment rates in 1970 were more able to improve quality through 1980 than countries that experienced rapidly growing enrollments in the 1970s (Fuller, 1987).
5.12 Improving access to and the quality of basic education is a priority in almost every low-income and middle-income country. In addition to being a highly productive investment in its own right, an effective basic education provides the literacy and numeric skills that are 50 Education and Development: Evidence for New Priorities necessary for all further education and training. In many countries, particular attention has to be paid to girls' education, which, even with school quality improvements, may not expand quickly without special attention to community and family barriers that impede girls' attendance.
5.13 Improved access and quality are inextricably linked: about 60 million of 400 million primary and secondary school places are occupied by repeaters. As much as 20 percent of education budgets is spent to teach repeaters and future drop-outs. In many countries, reducing repetition and improving quality across the board will require not only a different philosophy about the role of primary schooling (having all pupils reach relatively high standards of learning and achievement rather than acting as a gatekeeper-selector to keep most pupils from completing their primary education), but also additional budget allocations, and more efficient allocation of educational spending.
5.14 There is some evidence that improving student achievement in school or increasing school inputs (teacher quality) may have a higher economic payoff (as measured by increased earnings of school-leavers) than investing in additional years of schooling (Camoy, Sack and Thias, 1977; Behrman and Birdsall, 1983), and that improved school inputs may have more of an effect on student achievement in developing than in developed countries (Heyneman and Loxley, 1983; Solmon, 1985).
5.15 Assuming that the quality of school inputs could be improved through additional resources, how can schooling best be made more effective to increase student achievement? Since the United States' "Coleman Report" (1966), a large number of studies have addressed this issue in both developed and developing countries. The results of these "educational production functions" vary widely and are fraught with methodological problems, not least of which are that it is unclear what unit of production to use (individual pupil, classroom, school, school district) and whether the relevant unit of production is maximizing academic achieve- ment or some other output (Camoy, Sack, and Thias, 1977). Neither do any of the studies specify an underlying theory of learning that would define the nature of the school inputs- academic achievement relationship: they all assume that teacher inputs can be measured by teacher characteristics (education, experience, and aptitude), ignoring the way or the degree to which those characteristics are engaged in the teaching-leaming process (Levin, 1980).
5.16 Because of these limitations, educational production studies have produced inconclu- sive and often contradictory findings (Fuller, 1987). Nonetheless, some consistent general findings do emerge from these studies (see Table 25, page 51). First, variation in school inputs, such as teacher experience, teacher motivation, the presence of textbooks, homework, and time spent in school during the year do contribute to varying pupil achievement, even when family background differences are accounted for (Summers and Wolfe, 1977; Alexander and Simmons, 1978; Heyneman and Loxley, 1983; Fuller, 1987). Second, although the studies explain little of the total variance in individual achievement (which reflects the complexity of the teaching-learning process), they have been more successful in explaining variations in achievement among schools than within schools. Third, in lower-income developing coun- tries, the fact that there is much wider variation in school inputs than in middle-income and developed countries means that upgrading the amount of school inputs and the quality of the teaching process at the low end may raise academic achievement substantially (see also Zuzovsky, 1987, for a similar effect on low achievers in Israel).
5.17 However, educational production function studies have not been able to tell us accu- rately which school inputs have larger and smaller effects on achievement. Neither have they been particularly useful in identifying which inputs are more cost-effective than others -- although 'size" effects of the inputs are often a product of such studies, they rarely measure costs of inputs (for a review of cost-effectiveness of school inputs, see Lockheed and Hanushek, 1987). Education and Development: Evidence for New Priorities 51
Table 25. Improvingthe Qualityof Education:Selected EmpiricalStudies in DevelopingCountries
Study Data Base Results
Alexanderand A number of country Found no consistentinfluence of school Simmons(1978) studies relatingschool effects net of familybackground inputs and family backgroundvariables to school achievement
Fuller (1987) Large number of studies Variety of school inputs do contribute relating school to pupil achievement,but studies achievementto school tend to be atheoreticaland miss variablesin developing understandingprocess of schooling. countries
Lockheedand Studiesthat provide Radio and textbooksare more cost- Hanushek (1987) both effect-sizeand effective than teacher training. cost data on specific Academiceducation more cost- school inputs. Six effectivethan vocational. inputs reviewed, includingradio, text- books, and teacher training
Heynemanand Examinedthe influence Found larger effect of school factors Loxley(1983) of family background in lower-incomecountries than in and school factorson high-incomecountries. pupils' science achievementscores in 16 developingand 13 developedcountries Mostly IEA data base
Armitage,etal. Longitudinalsurvey of Teacherquality and instructional (1986) 4900 studentsover 2 materialshave significant years in NE Brazil rural effect on pupil achievement but schoolbuilding quality does not.
Thias and School data in Kenya Schoolcosts significant Carnoy(1972) (1968) on costs, in contributingto achievement boarding,class size at secondarybut not primary and averagestudent score level. Whetherstudents board on nationalexam at schooland teacher experiencealso significant.
Fuller and 27 thousandprimary Significantbut small effect Chantanavich schoolstudents in of teacher educationon pupil (1976) Thailanddata and school achievement. Teacherexpec- tations also have significanteffect.
Schiefelbein Pupil data in Chile School materialscontribute and Farrell (primaryand secondary to student achievementbut (1973) schools), individual not teacher education.Increased focus achievementand on homeworkhas positiveeffect. school inputs 52 Education and Development: Evidence for New Priorities
Table 25 (cont.). Improving the Quality of Education: Selected Empirical Studies in Developing Countries
Study Data Base Results
Carnoy (1971) School data on one- Significant effect of teacher quality on third of all public low-income pupils' achievement at school students in primary level. Length of school day Puerto Rico (1968) significant.
Haron (1977) 89 secondary schools Length of teacher training significant in in Western Malaysia, explaining student achievement. Class more than 7,000 size not significant. pupils
Carnoy and Four thousand pupils Teacher quality not significant in Thias (1977) in 16 Tunisian explaining value added to student secondary schools achievement (achievement relative to national final primary school exam). Boarding has positive effect on value added.
Loxley (1984) Survey of 869 School effects on reading and math students in 37 achievement greater than family schools in characteristics. Teacher training and Botswana library resources particularly important. Education and Development: Evidence for New Priorities 53
Table 26. Educationand Technology:Selected EmpiricalStudies in DevelopingCountries
Study Data Base Results
Radio and Education
Hall and Dodds Review of three radio Was useful in inculcatingcommunity (1977) campaignsin Tanzania health habits, awarenessof voting during 1969-1971. rights, etc.
Cassirer Senegal's UNESCO- Facilitateddialogue between peanut (1977) financed pilot radio farmers and government. project.
Suppe, et al. Nicaraguanradio Radio class pupils had better test scores (1978) mathematicsproject than those in controlgroups but grades 1-4 mathematics attendance,dropout, and repetition courses in the region were not affected. of Carazo and Rio San Juan provincesduring 1975-1978.
Hudson, Northernpilot project Increasedflow of informationinside and (1977) of Canada. outside the communities. Increased awarenessof regional interestsand activi- ties. Governmentbodies become more responsibleto local demands.
Oxford,et al. Kenyaradio language Helped elementarystudents perform (1986) arts project (1981- better in listeningand reading. 1984).
UNESCO Radio project in Radio instructionhad positive impact on (1976) Thailand. music,dancing, and singing, but no positiveeffect on social studies.
Jamison and McAnany Tarahumararadio Radio-instructedpupils performed (1978) schools: remote better in Spanishand math. region in Chihuahua Mexico during 1957-1972(did not continueafter 1972).
Walker (1986) Radio-assisted Low cost and cost-effective,relative to community-based traditionaleducation (preliminary education,Dominican findings). Republic.
White (1977) Popularcultural Literacy was not a priority for peasants. action of Honduras: They preferredoral programs. ACPH radio schools for peasants.
Spain, Jamison, Seriesof case Radio generallyhighly effectivein and McAnany(1977) studies. achievingvariety of educationalobjec- tives at low cost. 54 Education and Development: Evidence for New Priorities
Table 26 (cont.). Education and Technology: Selected Empirical Studies in Developing Countries
Study Data Base Results
Anzalone (1987) Review of studies on Radio when properly used can education and media. be an effective way to improve student achievement in a variety of subjects. Also relatively cost-effective.
Television as an Educational Medium
Schramm, et al. American Samoa High $166/pupiVyear cost. (1981) television-assisted No significant effect on student instruction. performance after seven years. Resis- tance by teachers result of noninvolve- ment in planning.
Clearinghouse on The Niger experimental High $1156/pupil/year cost. development Teacher training program. Reduced dropouts from 40 percent communication to 4 percent. (1982)
Kaye (1976) Ivory Coast. Started $13/pupiVyear. Improved spoken in 1971 (funded by French. Maintenance a serious World Bank, presently problem. Ultimately failed. discontinued.)
Mayo, et al. (1976) El Salvador. Expanded opportunity for secondary education. Cost: $26/studentyear in 1972. The ETV students fared better than non-ETV students in 7th but not in 8th and 9th grades; in mathematics but not in sciences and social science (Mayo). Boys made larger achievement gains than girls.
Schramnm(1967) Colombia $4/pupil/year. There was no significant educational performance gain by ETV students television. relative to non-ETV students except in grade 2 (language), grade 5 (math), and grade 4 (natural science).
Shukla (1979) Satellite instructional Centralized programs did not address TV experiment for local cultural milieu. Program helped in disadvantaged pupils' language development. children
Anzalone (1987) Review of existing Use of television is expensive and studies, contributes little to pupil achievement. Education and Development: Evidence for New Priorities 55
Table 26 (cont.) Educationand Technology:Selected EmpiricalStudies in DevelopingCountries
Study Data Base Results
Computersand Education
Carnoy,et al. Review of available Developingcountries are enteringinto (1986) studies. computerliteracy investmentprograms that are based more on nationalistic rhetoric than concrete cost-benefit analysisor even educationalrationale. Main gainsin programmingskills in developedcountries are usually made by students with computersat home.
Papagiannis Reviewof existing Cost-effectivenessstudies in the U.S. (1987) studies. suggest that computersraise achievement, but are expensiverelative to other media.
Becker (1987) U.S. elementary About 77% of the time used in schools. computerswas for drill and practice in reading,language arts, and arithmetic. By 1985, five out of six primaryschools had computersfor instruction(an esti- mated 1 computer/40pupils in 1987)and a majorityof high schools had 15 or more computersfor instruction.
Williams(1987) Computersand gender Within schools where computerswere gap. Trinidadand used in instruction,females had greater Tobago. access than males, but outside of school, males had greater access.
Kulik, Kulik and Effects of computer- Computer-assistedinstruction Bangert-Drowns assisted instruction. has positive effect on the achievementof (1985) A meta-analysisof primary schoolstudents in various 32 research studies. school subjects. Average effect size of 0.47 (consideredhigh).
Levin, et al. Pre- and posttest For a schoolwith a fully equipped (1984) data on students in computerlaboratory in the U.S., the computerinterventions cost would be $119/student/year(1980 in U.S. primary estimate);hardware only a small schools. fractionof total cost. Positive effect on pupil achievement,but less cost-effective than peer tutoring.
Freeman (1987) Computer-classroom The use of computersis significantly ethnographyin one disturbedby poor electricalsupply. primaryschool in Grenada. 56 Education and Development: Evidence for New Priorities
Table 27. ImprovingSector Management: Selected EmpiricalStudies in DevelopingCountries
Study Data Base Results
Fuller (1987) Several schoolquality Headmastereducation and studies that include experienceappear to have managementvariables significantpositive effect on in models explaining pupil achievement. pupil achievement
Heynemanand Studentsin 60 Studentsperform better in schools Loxley (1983) Egyptianprimary with principalswho had attended schools more trainingcourses.
Sembiringand Studentsin 124 Studentachievement strongly Livingstone Indonesiansecondary associatedwith headmasters' (1981) schools salary and teaching experience.
Morales and Studentsin 53 Signficantrelationship Pinellsiles primaryand second- betweenstudent achieve- (1977) ary schools in ment and headmasterpost- Bolivia secondaryeducation.
Figueroa(1986) In-classobservations Principals' management styles, in 5 primaryschools curriculum,and classroom in MexicoCity organizationdiffer markedlybetween public and private schools.
Technology in Education
5.18 For this reason, partial cost-effectiveness studies of particular educational inputs have often yielded more interesting and directly applicable results. World Bank research has focused on low-cost inputs, such as textbooks (Heyneman, 1980) and radio (Spain, 1977; Jamison, 1978; see also, Block, 1985; Friend and Koslow, 1985; Ministry of Education of Ethiopia, 1987; a summary of instructional hardware applications in developing countries by Anzalone, 1987). These have shown relatively high effectiveness-cost ratios compared to traditional inputs -- particularly radio and textbooks (Lockheed and Hanushek, 1987). In the United States, similar studies comparing peer-tutoring, adult-tutoring, and computer-assisted instruction show that all three forms of augmenting traditional education show positive effects on student achievement, but that peer-tutoring is by far the most cost-effective (Levin, et al., 1984). A sample of available empirical research on educational technology is presented in Table 26, page 53.
5.19 The results of such research suggest that in many low-income countries facing an increasing knowledge gap, additional school inputs, such as textbooks and radio, and addi- tional delivery methods such as peer tutoring and more effective curricula and teacher-student interaction, have to be considered seriously as a way to reduce that gap in the next decade. But we need to know more, particularly about more effective curricula and methods of delivering formal schooling and teacher training.
Sector Management
5.20 More recent studies suggest that school management may also be a high yield resource in improving student achievement. Until now, production function studies of school- Education and Development. Evidence for New Priorities 57 ing -- which should reveal how to use existing resources more effectively -- have focused on relating school inputs to pupil achievement. But many of those who have observed the schooling process in both developed and developing countries conclude that the most impor- tant factor governing how well pupils do in school is school management (Table 27, page 56), which, in many developing country rural schools, is often dependent on either a single teacher or a school principal, the curriculum which the teachers use, the availability of textbooks and other teaching aids (which often depend on the cleverness of the teacher in making use of available resources), the amount of effort that teachers are willing to expend, and the involve- ment of the community in making learning and academic achievement a community goal. Except for the availability of textbooks, none of these factors (which we can describe as the "process" of schooling) enters into school production estimates.
5.21 Management is singularly important in defining the "charter" (or standard of excel- lence) of the school (Figueroa, 1986) and the charter, in turn, is crucial in defining how well students are expected to do (Meyer, 1970). Levin (1980) argues that curriculum and other management decisions -- many of them highly centralized -- also define the way and the amount that teachers teach, as well as class size, which leaves relatively little autonomy for the non-innovative teacher. Figueroa claims that in Mexican public schools, the principal spends most of his or her time dealing with the Ministry rather than with problems in the school. Several studies have identified headmaster education and experience as important variables that affect pupils' achievement (see Table 25, page 51). Recent reports on schooling in the United States, such as A Nation at Risk, or Goodlad's A Place called School, have also focused on school management -- particularly on principals, superintendents, and other school "lead- ers" and innovators.
5.22 We know that well-managed, effective schools share several characteristics: they display an orderly environment, emphasize academic achievement, set high expectations for student achievement, and are run by teachers or principals who expend an enormous amount of effort to produce effective teaching and encourage pupils to learn, no matter what their family background or gender. Few schools in developing countries display these features. But we know little about why that is the case or what steps to take to provide greater and more effective effort. Particularly in low-income countries, these steps should be based on low-cost strategies.
5.23 The World Bank's Education and Employment Division in the Population and Hu- man Resources Department (PHR) is now undertaking a case study approach of effective schools in low-income and middle-income countries. This will go far in providing further information. A more careful analysis of low-cost, effective approaches to formal education, especially those that involve parents and the community and new kinds of curriculum, teacher training, and educational management, could yield important new evidence that could improve learning in low-income countries and regions.
5.24 In addition to such case studies, further information could be derived from a review of educational management studies. Many of these studies propose management models for education, or focus on the use of technology for better educational management at the ministe- rial planning level. The World Bank's focus in recent years has implicitly been on manage- ment models that tend to centralize control over curriculum and quality through educational media (especially radio); that is, such models implicitly attempt to make the leaming process "teacher proof" as they simultaneously attempt to keep costs of improved quality low. But what is needed is an analysis of management models that work at the school level, especially in primary schools, to test if such alternatives could be even more effective than educational media or make the use of educational media and other inputs (textbooks, for example) more effective. 58 Education and Development: Evidence for New Priorities
Science Education
5.25 The current changes in the world economy suggest that a strong preparation in sci- ence and mathematics education will be increasingly indispensable to improved productivity and economic development, as well as opening new possibilities for families to raise the quality of their everyday life. There is no evidence for this assertion beyond the higher salaries earned by those who specialize in scientific and technical fields. But, intuitively, it seems likely that the problem-solving approach to life and work situations that is conveyed by science and math education (when it is taught well) should serve economic and social develop- ment goals particularly well.
5.26 Low achievement in science and math and unfamiliarity with basic technical concepts are critical weaknesses throughout the developing world. This particularly hurts the ability of countries to absorb new technologies that help increase productivity. It also hurts countries in developing their own appropriate innovations to solve production problems on a day-to-day basis.
5.27 There are a number of different approaches to the teaching of science and math, and we need to know more about the pluses and minuses of such approaches. For example, there is a long-running debate in the developing countries about what (and therefore how) science and math should be taught and leamed (King, 1985). Those who focus on a more traditional scientific curriculum argue that the principal reason for low science and math achievement in low-income countries is that there is a dire shortage of qualified science and math teachers. If that is the case, it may be possible to overcome the shortage by applying new technologies that provide opportunities for self-study to large numbers of students outside and within the tradi- tional educational system. In the industrialized countries, it is being argued that computers in the classroom can and will greatly increase the efficiency of science and math instruction (U.S. Congress, Office of Technology Assessment, 1988; Raizen, 1988). Pilot programs in develop- ing countries have demonstrated convincingly that traditional "low-tech" technologies such as radio can also enrich and improve instruction in math as well as in language, once the basic conditions for orderly teaching and learning have been established (Suppe, et. al., 1978).
5.28 But others contend that the main reason for low achievement is not the lack of adequately skilled teachers, but the inappropriateness and inefficiency of a curriculum that requires scientific knowledge and practice far from any local experience (see King, 1985). The science and math curriculum is imported. It does not take advantage of a great deal of scientific knowledge and mathematics capability in local communities. In addition, the sci- ence and math problems posed to pupils have little to do with local applications. Science and math is often not taught through problem-solving at all, but through rote memorization.
5.29 This debate can be documented with a review of literature and case studies. What is needed is a better foundation for understanding what assumptions lie behind many of the assertions and what evidence there is for the effectiveness of altemative approaches to improv- ing science and math education in different development situations. We need to learn from UNESCO's experience in this field. And more information is needed about the spectacular student math and science results achieved by countries such as Japan, Hong Kong, and the Republic of Korea.
Higher Education, Scientific Research and Development, and Technology Transfer
5.30 Intuitively, it would seem that those countries with a greater number of scientists and engineers -- especially if they are involved in research and development -- have a much greater possibility of adapting and developing new technologies (Rosenberg, 1982; Bianchi, Carnoy, and Castells, 1988). There has been great concem in the United States, for example, that poor Education and Development: Evidence for New Priorities 59 science and mathematics preparation on a broad scale in public school will handicap the United States' economic development relative to its principal competitors in the future (National Science Foundation, 1980; U.S. House of Representatives, 1983).
5.31 Because they are leaders in scientific innovation and their economic development depends on translating this innovation into higher productivity and new products, the industri- alized countries are especially concerned with the relationship between higher education (training), scientific research, and the application of research results and training to the produc- tion of goods and services (technological diffusion). For these countries, finding the most effective model for building research capacity and high level training and linking them for conmnercial applications has a potentially enormously high payoff in increased economic growth. The NICs, some middle-income countries, and the larger low-income countries, such as India and China, which already have a significant scientific base, are also concerned about expanding their research capacity and translating it into more efficient and innovative produc- tion of goods and services for domestic consumption and especially for export. Finding the proper role for university-level training and research is fundamental to transforming these countries' production processes. At the same time, most low-income countries need to de- velop the scientific personnel who will understand fully the latest technological advances coming out of the industrialized countries and be able to adapt and apply them for local production of goods and services. These countries must therefore also be concerned about delivering high-quality university education -- even for a relatively small number of youth -- and its relationship to research and development, especially for the packaging of new (and old) technologies for local applications.
5.32 Cross-section and case studies provide convincing evidence that access to knowledge and technology, as well as social and political factors, are crucial to technological diffusion (Edquist, 1985; Edquist and Jacobsson, 1988). An important element in access to knowledge and technology is education. But understanding the nature of the relationship between educa- tion -- particularly higher education -- and technology transfer requires more informnationand evidence. Some will emerge from the present review of research on higher education by PHR's Education and Employment Division. More can be found through an analysis of case study research on technology transfer in developing countries (see, for example, Bianchi, Camoy, and Castells, 1988).
5.33 The important issue in both reviews is the role of university technical and scientific education in technological diffusion, and whether there are mediating factors in converting high-level scientific and technical skills into increased productivity through new technology. These mediating factors could include the nature of university science, math and engineering curriculum (problem solving versus memorization), the link between university and industry (practical applications), the link between training programs and research and development, or the general economic, social and political conditions for innovation and innovative applica- tions. The case of the Soviet Union stands out as one in which a massive program in scientific and technical education has not translated into rapid and widespread technological diffusion. Japan and the Republic of Korea are counter-examples.
5.34 One of the clearest indications of the gap in developing nations' capability of moving into the age of information technology is the relatively small fraction of the labor force with scientific and engineering education and the even smaller relative fraction of scientists and engineers involved in research and development in those countries.
5.35 Table 28, page 62, shows the enormous variation in the ratio of scientists and engi- neers (and technicians) per 1,000 of economically active population, as well as the high con- centration of scientific and engineering manpower in high-income, technologically-advanced economies. More than 80 percent of all research and development manpower is found in five 60 Education and Development: Evidence for New Priorities countries. And the countries that have shown the greatest advances in technology creation and adoption in recent years are those with the highest ratios of scientists and engineers. Neverthe- less, the example of the Soviet Union, with its large scientifically and technically trained labor force but relatively inefficient and technologically backward manufacturing and services, indi- cates that scientific education alone is not enough to produce highly diffused technological change.
5.36 Although this is "circumstantial" evidence of the importance of science and technical education as a necessary, if not sufficient condition, for the diffusion of technology, it does suggest that future educational policy for economic development will focus much more on the capability of the educational system to produce highly qualified scientists, engineers, and technicians, as well as the private and public managers who can work with them in applying technology to production and services. In addition, there will be a greater focus on creating a .scientific outlook" in the broad base of developing societies. This implies that the quantity and quality of science and mathematics education (as measured in terms of what children learn) -- from the basic to university levels has taken on increased importance as the world economy shifts to information technology.
5.37 Another issue is whether the key elements of appropriate and efficient university education and its linkages to industry and research can be reproduced through lower-cost forms of higher education in order to achieve a similar impact on technology diffusion and increased productivity. Most of the research on "distance education," for example, has focused on its cost-effectiveness (Perraton, 1982) and the mechanics of using of technology in providing such distance education (Asian Development Bank, 1986). But what are the possi- bilities of distance education in increasing technological diffusion and innovation? Can the key elements of effective scientific and technical education for technology transfer be repro- duced through non-traditional, lower-cost forms of higher education?
Educational Finance Reform
5.38 The present distribution of public expenditures on education is highly unequal. The relatively few individuals who gain access to higher education receive more subsidies (in absolute terms) than those at the lower levels (World Bank, 1986; Jallade, 1973; Jallade, 1974; Mingat and Tan, 1986). Jallade's early research in Colombia and Brazil showed that lower- income groups are taxed to subsidize higher-income groups' education, this primarily because of students' highly unequal social class distribution across different schooling levels and the much higher cost-per-student at higher levels of schooling. A more recent Bank study shows that even among students who finish secondary school and pass the entrance examination for university entry, those who actually enroll have lower test scores but much higher social class background than those who do not (Jimenez, 1986). This pattern of subsidies also exists within the university level in developed countries (Hansen and Weisbrod, 1969; Levin, 1987) and in developing countries (Yao Yao, 1987): lower social class students are more likely to attend lower cost, lower-esteemed universities when there exist within-country variations in university cost and -quality," and are likely to specialize in lower cost humanities faculties rather than high cost and high payoff engineering, law, or medicine.
5.39 Inequality in educational spending is substantially greater in the developing countries than in the developed (see World Bank, 1986, Table 11, reproduced here as Table 29, page 64) and greater in Sub-Saharan Africa than in Asia or Latin America. The higher the average level of schooling, the lower the inequality in spending. But developed countries and Latin Ameri- can countries also tend to spend more per student on primary schooling than do Asian and Sub-Saharan Africa countries. Sub-Saharan Africa countries also have the highest ratio of university to primary cost-per-student. Furthermore, Latin America has drastically reduced spending per student at the secondary and especially the tertiary level relative to the primary Education and Development: Evidence for New Priorities 61 level in the 1970s (Heller and Cheasty, 1984). These data do not account for differences in taxes paid by different groups, but, as Jallade shows, even accounting for higher taxes paid by higher-income groups, education generally provides a net transfer from lower-income to higher-income families.
5.40 As a response to high costs-per-student at the university level and this inequality in educational spending, the Bank has already produced a number of suggestions for financial reform (see Table 30, page 65). Studies have focused primarily on cost recovery (especially at the university level), reinvesting the recovered costs in lower levels of schooling to increase equity, and decentralizing education, particularly in order to encourage the mobilization of family resources through community contributions to public schools and the formation of private schools (World Bank, 1986).
5.41 Cost recovery schemes at the university level are appealing, particularly in Sub- Saharan Africa, where university spending-per-student may be 60 times as high as per primary school student, and there is a large excess demand for university places. Much of this cost in most Sub-Saharan Africa countries, furthermore, is in the form of student living allowances (World Bank, 1986). Eliminating student allowances and even charging tuition combined with student loan programs therefore seems a logical scheme to reduce public costs substantially and simultaneously reduce excess demand. The funds created by cost recovery could be reinvested in improving or expanding university education or in other levels of schooling -- the latter would be most efficient should the rate of return to lower levels of schooling be signifi- cantly higher than to university. Reinvestment in the primary level would achieve greater equity.
5.42 Critiques of university and secondary school cost recovery schemes have identified three principal problems: (1) The political problem -- they hit hardest at the politically vocal urban professional and middle classes. (2) The economic efficiency problem -- in many countries, the rate of return to investment in university and secondary education is high and higher than to the primary level. Further, even in those countries where the social rate of return does not justify large public investment in university education, future economic devel- opment may depend on an underlying infrastructure of highly trained scientists, engineers, and technicians. This would require selective cost recovery, focusing on students less economi- cally valuable humanities, social sciences, and so forth. These are usually students from lower-income families. (3) The equity problem -- as Jimenez's work in Colombia (1986) suggests, even with a student loan program, lower-income students are less likely to attend university unless motivated with financial subsidies. A cost recovery scheme is therefore likely to reduce equity unless the public sector used recovered costs specifically to improve lower levels of schooling. There is no available evidence that such a shift has or would occur.
5.43 One reason that universities are especially expensive in Sub-Saharan Africa, aside from excessive living allowances, is that they are plagued by significant diseconomies of scale (Psacharopoulos, 1982). This suggests that there is considerable room for making universities more cost-effective by regionalizing certain expensive specialties and by developing altema- tives to traditional, European-style university education (discussed below). The need to re- gionalize programs for lower-income, smaller countries is crucial if they hope to develop the creative and decisionmaking technical talent to adopt and modify high technology for local applications. The same is true for research and development programs. This requires more, not less, investment in higher education and research, but in a more cost-effective manner and one that probably transcends national boundaries.
5.44 Privatization is another appealing way to softening reduced public educational spend- ing. It promises to mobilize private resources that would not be forthcoming in an entirely public system, because of the touted greater cost-effectiveness of private education (see, for 62 Education and Development: Evidence for New Priorities
Table 28. Scientific and Technical Personnel by Level of Development
Econ. R&D Sci. Sci. & Tech. Potential Active Pop. Total Techs. Sci/Eng. Total Tech. Sci/Eng. Country Year ('000) ('000) ('000) ('000) ('000) ('000) ('000)
GROUP A: Primary Product, Low-Income Burundi 1961/1984 2,654 0.3 0.1 0.2 - - - Nepal 1981/1981 10,518 0.4 0.1 0.3 11.0 7.3 3.7 GROUP B: Marginally Industrialized, Middle-Income El Salvador 1980/1980 1,622 1.6 - - 7.3 1.8 5.5 Guatemala 1985/1984 2,254 2.7 - - 12.7 7.1 5.6 Pakistan 1984-5/1986 28,872 23.3 14.0 9.3 100.5 - 100.5 GROUP C: Industrializing, Middle-Income, High Education Costa Rica 1985/1982 887 0.4 - 0.4 - - - Cuba 1986/1985 3,540 19.5 9.2 10.3 139.5 - 139.5 Egypt 1983/1982 13,842 26.6 6.7 19.9 492.5 - 492.5 Indonesia 1985/1984 63,826 29.0 4.1 24.9 2,104.8 1,911.5 193.3 Peru 1981/1981 5,314 4.9 - 4.9 1,689.8 1,398.0 291.8 Sri Lanka 1985/1983 5,972 3.3 1.4 1.9 18.5 11.0 7.5 Zimbabwe 1982/1982 2,484 0.9 - - - - - GROUP C-1 China 1982/1982 524,907 27.0 - - 7,466.0 - India 1981/1982 244,605 93.7 - - 1,949.0 - - GROUP D: Oil Exporters, Upper-Middle and High-Income Iran, Isl. Rep. 1982/1982 6,418 5.1 1.9 3.2 465.5 170.9 294.6 Nigeria 1983/1977 29,453 3.5 1.3 2.2 133.8 111.7 22.1 Venezuela 1986/1983 6,107 7.3 2.7 4.6 1,881.0 1,534.0 347.0 GROUP E: Newly Industrialized Argentina 1985/1982 11,452 10.5 - 10.5 2,232.1 1,696.4 535.7 Brazil 1985/1982 55,098 32.5 - 32.5 4,436.6 3,074.4 1,362.2 Chile 1985/1984 4,236 1.7 0.1 1.6 69.9 - 69.9 Cyprus 1985/1984 249 0.2 0.1 0.1 - - - Greece 1983/1983 3,892 3.5 1.1 2.4 1,602.1 1,272.6 329.5 Israel 1986/1986 1,472 53.7 14.0 39.7 146.1 63.8 82.3 Korea, Rep. of 1986/1983 16,116 51.6 19.5 32.1 2,025.6 1,931.5 94.2 Malaysia 1980/1980 4,260 2.7 - - - - 26.0 Mexico 1980/1984 22,066 46.6 29.5 16.7 - - - Singapore 1986/1984 1,229 3.8 1.4 2.4 64.2 25.9 38.3 Yugoslavia 1981/1981 9,359 38.7 13.8 24.9 3,986.0 3,584.0 402.0 GROUP F: Industrialized Australia 1986/1981 7,481 36.2 12.0 24.2 2,093.0 1,709.6 383.4 Austria 1986/1981 3,388 12.8 6.1 6.7 153.9 - 153.9 Canada 1986/1984 12,870 57.1 20.6 36.5 7,042.6 5,802.1 1,240.4 Denmark 1985/1983 2,753 17.8 10.3 7.5 323.7 240.2 83.5 Finland 1985/1985 2,598 23.6 - - 1,616.6 1,444.4 172.2 France 1985/1979 24,085 230.9 157.9 72.9 1,251.6 - 1,251.6 FRG 1985/1983 29,012 252.7 119.6 133.1 8,374.0 2,278.0 6,096.0 Italy 1986/1983 23,617 91.7 28.7 63.0 4,703.4 3,527.9 1,175.4 Japan 1985/1984 60,391 628.7 97.1 531.6 37,050.0 30,004.0 7,046.0 New Zealand 1981/1981 1,332 8.1 - - 139.5 92.3 47.2 Spain 1986/1984 13,781 21.5 6.2 15.3 4,634.8 3,482.8 1,152.0 Switzerland 1985/1983 3,201 13.4 - - 348.2 - 348.2 United States 1986/1983 119,540 728.6 - 728.6 3,431.8 - 3,431.8 USSR 1986 185,526 1,463.8 - 1,463.8 31,628.0 18,141.0 13,487.0 Education and Development: Evidence for New Priorities 63
R & D Sci. PotentialSci./7ech. Manpower Per 1,000Eco-Active Pop. Per 1,000 Eco-ActivePop.
Total Tech. Sci,Eng. Total Tech. Scl/Eng. ('000) ('000) ('000) ('000) ('000) ('000)
0.1 0.0 0.1 - - - 0.0 0.0 0.0 1.1 0.7 0.4
1.0 - - 4.5 - - 1.2 - - 5.7 3.2 2.5 0.8 0.5 0.3 3.5 - -
0.5 - 0.5 - - - 5.5 2.6 2.9 39.4 - 39.4 1.9 0.5 1.4 35.6 - 35.6 0.5 0.1 0.4 33.0 30.0 3.0 0.9 - 0.9 318.0 263.1 54.9 0.5 0.2 0.3 2.0 1.8 0.2 0.4 - - - - -
0.1 - - 14.2 0.4 - - 8.0 - -
0.8 0.3 0.5 72.5 26.6 45.9 0.1 0.0 0.1 4.6 3.8 0.8 1.1 0.4 0.7 308.0 251.2 56.8
0.9 - 0.9 194.8 148.1 46.7 0.9 - 0.6 80.5 55.8 24.7 0.4 0.0 0.4 16.5 - 16.5 0.5 0.3 0.2 - - - 0.9 0.3 0.6 411.7 327.0 84.7 36.5 9.5 27.0 99.4 43.4 56.0 3.2 1.2 2.0 125.7 119.8 5.9 0.6 - - 6.1 - - 2.1 1.3 0.8 - - - 3.1 1.1 2.0 52.3 14.1 38.2 4.2 1.5 2.7 426.0 383.0 43.0
4.8 1.6 3.2 279.7 228.5 51.2 3.8 1.8 1.9 45.4 - 45.4 4.4 1.6 2.8 547.1 450.8 96.3 6.5 3.7 2.7 117.7 87.3 30.4 9.1 - - 622.3 556.0 66.3 9.6 6.6 3.0 52.0 - 52.0 8.7 4.1 4.6 288.6 78.5 210.1 3.9 1.2 2.7 199.2 149.4 49.8 10.4 1.6 8.8 613.5 496.8 116.7 6.1 - - 104.8 69.3 35.5 1.5 0.4 1.1 336.3 252.7 83.6 4.2 - - 108.8 - 108.8 6.1 - 6.1 28.7 - 28.7 7.9 - 7.9 170.7 97.8 72.9 64 Education and Development: Evidence for New Priorities
Table 29. Share of Cumulative Public Educational Expenditure Appropriated by Various Socioeconomic Groups, 1980
Percentage in the Percentage of educational population expenditure appropriated Appropriation ratio (1) (2) (2)1(1)
Rural Manual White- Rural Manual White- Rural Manual White- Region workers workers collar workers workers collar workers workers collar
Anglophone Africa 76 18 6 56 21 26 0.73 1.19 3.78 Francophone Africa 76 18 6 44 21 35 0.58 1.15 5.93 Asia 58 32 10 34 38 28 0.59 1.19 2.79 Latin America 36 49 15 18 51 31 0.49 1.04 2.03 Middle East and Africa 42 48 10 25 46 29 0.60 0.35 2.87 Developing countries 58 33 9 36 35 29 0.60 0.98 3.48 Developed countries 12 53 35 11 46 43 0.95 0.87 1.20
The number of countriesincluded in each region is given in appendixtable 14.
Source: World Bank, 1986, Financing Education in Developing Countries.
example, Psacharopoulos, 1987; Jimenez, 1986; Jimenez, Lockheed and Wattanawaha, 1988), and because increased competition between private and public schools may make public schools more efficient.
5.45 A number of developing countries -- for example, the Republic of Korea, the Philip- pines, Thailand, Brazil, and Kenya -- have highly developed private systems of education catering to students from both high-income and low-income families. There is no question that private education mobilizes additional family resources, but little evidence that this pro- motes the public sector to invest the additional resources made available in more or better public schooling or that public schooling becomes more efficient as a result. Increasing the private costs of education through privatization (even through increasing school fees) may also reduce female enrollment, particularly where families value female education less than male education (Smock, 1981).
5.46 In Brazil, a private university system subsidized by the state was allowed to expand in the 1970s to absorb excess demand, especially from lower academically able (and lower- income) secondary graduates. These "diploma mills" absorbed excess demand by "taxing" lower-income families to take bank loans and pay tuition, while higher-income families continued to send their children to excellent public universities. Neither did the Brazilian government plow the resources released into a rapid expansion or increased quality of lower schooling levels. Brazil continued to invest a relatively small percentage of its GDP in education.
5.47 Although there are many examples in which private education is more efficient than public in producing high academic achievement (Jimenez, 1986; Jimenez, Lockheed, and Wattanawaha, 1988), there are also serious questions about the general validity of many of these studies (Levin, 1987). Counter-examples also exist, notably the large system of Education and Development: Evidence for New Priorities 65
Table 30. AlternativeFinancing Approaches: SelectedEmpirical Studies of Cost Recoveryand PrivateEducation in DevelopingCountries
Study Data Base Results
Cost Recovery
World Bank, Surveyof studies on Cost recovery and fee-basedprivate FinancingEducation cost recovery and educationhave small negative impact in Developing impact of private on attendanceand could mobilize Countries(1986) education considerablefamily resources for education. Possiblepositive impact on equalizingdistribution of school spend- ing.
Mingat and Tan Publisheddata on Simulationof student loan repayment (1986) universitygraduates under various assumptionsof earnings; university completionrates and loan conditions enrollment suggests that with small loans, even in Africa,university student loan schemes would recouppart of public costs. In Asia and Latin America,a high percent- age of costs could be recovered.
Woodhall(1983) Secondarydata on Studentloans are availablefor funding student loans, by universityeducation in 30 countries;the country,world-wide programsappear to be successful.
Jimenez (1987) Data from household Estimatedprice and elasticitiessuggest surveys on spending that averagerate of enrollmentmight for education not fall if fees increase,although different income groupsmay be affecteddiffer- ently.
Kulakow,Brace, Case studies of School gardenscan produceoutput and Morrill mobilizingcommunity that could offset school costs. (1978) resources for education
Gustafsson Case studies of edu- Productionby pupils in school (1988) cation with production productionunits not an important in Botswanaand cost-factor. Zimbabwe
Tan, et al. Three thousandprimary Estimateddemand functions for (1984) and secondaryschool educationsuggest that user fees will students in Malawi have small effect on enrollment,but larger for low-incomefamilies.
Private Education
Schiefelbein(1985) Studentsin private Privateschool students achievedmore and public schools academicallyin Chile in 1982 than those in state schools, even when differencesin social class are taken into account.
Jimenez (1986) Studentsin private Privateschool students achievemore and public schools academicallyeven though unit costs in Bolivia and Paraguay; in private schools are lower than in state school costs schools. 66 Education and Development: Evidence for New Priorities
Table 30 (cont.). Alternative Financing Approaches: Selected Empirical Studies of Cost Recov- ery and Private Education in Developing Countries
Study Data Base Results
Jimenez,Lockheed, Sample of four thousand Studentsin private schools perform and Wattanawaha 8th grade students and significantlybetter than their public (1988) 99 math teachersin schoolcounterparts and private schools Thailandin private and are also more cost-effective. public schools
Coleman,et al. Surveyof students in Catholicschools are more effectivethan (1982) United States in public schools in helping students public and private acquirecognitive skills. Catholic schools
Psacharopoulos(1987) Sample of six thousand Privateschool students in Colombia Colombianand four seem to do better in academic subjects, thousandTanzanian but results are mixed. In Tanzania, secondarypublic and private schoolstudents do worse. Cost private schoolstudents of private schoolingis lower.
'Harambee" schools in Kenya (Armitage and Sabot, 1985), whose graduates score much lower on national examinations and do much worse in the labor market than public school graduates. But an additional and crucial issue is whether private schools can satisfy the underlying social (public) goals of public education (Levin, 1987), such as bringing students from widely vary- ing backgrounds into a common national social experience called the public school. In the case where public secondary schools cater to higher income, better academically prepared students, it is true that privatizing education may make education as a whole more accessible and effective for the poor (this is in part the Jimenez, Lockheed, and Wattanawaha (1988) argument). But in the case where the better students tend to go to private schools, privatizing education could take the pressure off the Ministry of Education to improve public education, reducing access for low-income families. 6 Conclusion
Where More Work is Needed
6.1 This review suggests that there is a wealth of data from which to develop relevant policy approaches to education in the 1990s. The relation between education and economic development is well documented. More than enough information is available to analyze the changes that have taken place, worldwide and in countries at different levels of development, in school enrollments, retention, and school finance. The experiences of the lending institu- tions in educational assistance are also available in great detail. And a number of crucial educational policy areas, such as vocational versus academic curriculum, improving the effi- ciency of the schooling process, technology in education, and alternative forms of financing education, have been extensively studied empirically. These empirical studies provide a rich source of results for policy direction. We can already draw a number of conclusions for such new policy approaches.
Education and the Changing International Division of Labor
6.2 As new technologies and production processes transform the international economy, the future of world development and of individual nations' places in it hinge much more than even a generation ago on the capacity to acquire, transmit and apply knowledge to work and everyday life. The production of manufacturing and high-valued services no longer filter down "naturally" from high-income to low-income countries based on labor costs alone. Because of new goods, such as consumer electronics, and new processes, such as numerically- controlled machine tools and computer-assisted design and manufacturing (CAD-CAM), the location of manufacturing and high-value services depends increasingly on the producers' capacity to control quality and manage flexible, information-based systems. Comparative advantage is now a function of labor and management quality, as well as low wages.
6.3 There is already compelling evidence that a well-educated labor force is critical to the success of economic policies promoting international competitiveness and sustained develop- ment. And investments in education are not only central to economic growth, they also further the effectiveness of investments in family planning, health and nutrition.
6.4 There is compelling evidence as well that increasing access to education contributes positively to more equitable income distribution and to reducing poverty. In the words of Nobel Prize-winning economist, Theodore Schultz, "... the decisive factors of production in improving the welfare of poor people are the improvement in population quality and advances in knowledge." Private and social benefits from incremental outlays on education are highest in the poor countries, and, in those countries, are highest for outlays on expanding and improv- ing basic education, precisely the level which targets the most disadvantaged groups. Basic education imparts essential knowledge. But it also develops crucial attitudes and values --
Education and Development: Evidence for New Priorities 67 68 Education and Development: Evidence for New Priorities especially a sense of self-efficacy, or "can do" -- needed to adopt new methods and adjust to rapid change. Thus, the sustainability and long-term effectiveness of other programs that target disadvantaged groups -- such as those that address issues related to safe motherhood, population, women in development, and the alleviation of poverty -- also hinge on the quality of educational opportunities available to these groups. Of special importance is the education of girls who are often faced with socioeconomic and cultural obstacles that make attending school difficult for them.
6.5 Now, however, with the revolution in information, biological transformation and materials sciences, every country's educational system has become fundamental to its national production and the way it participates in this changing international economy. The new tech- nologies and production methods offer enormous possibilities for increased agricultural and industrial output. But they depend much more than previous technologies and methods on well-trained, flexible labor; innovative, problem-solving management; and cadres of highly- trained scientists, engineers, and social scientists, including some with sophisticated research skills needed to understand fully developments at the frontiers of knowledge and to assess how such advances can be applied locally. As technical requirements increase, more and better education -- particularly good science and math education at all levels -- is needed to develop that all-important attitude of "can do," as well as to impart essential knowledge and skills that allow adaptability and flexibility in the ever-changing job environment. More than ever, an educated population is needed to develop and apply emerging technologies appropriately to meet local development needs.
6.6 This is a challenge that confronts all economies participating in the world system. Preparing for a future marked by increasingly rapid science-based change means developing human resources that can respond to change with the necessary information and decisionmak- ing capability.
The Knowledge Gap
6.7 Just when more and better education is needed, much of the world's population is being left behind. Future workers and parents in poor countries should be getting a greater understanding of their physical and social environment. They should be increasingly capable of using information to improve the quality of their lives. They should even be catching up to industrial-country workers in what they know and in getting the opportunity to use it. Some are catching up. But, on average, differences in the acquisition of such knowledge -- the 'knowledge gap" -- appear to be increasing between wealthy and poor economies, and, in many places, between the wealthy and the poor within countries.
6.8 One way to get a grip on the knowledge gap and how it is changing is to look at school enrollment and school quality across countries and over time.
6.9 Both governments and international donor agencies have invested heavily in education during the last three decades, producing impressive expansions of enrollment throughout the developing world at all levels of education. Yet the enrollment gap between the lowest-income countries and other countries widened during 1980-85. In high-income and middle-income countries gross enrollment ratios were at or above 100 percent by 1985. In the lowest-income countries, the ratio at the primary level rose from 38 percent in 1960 to 65 percent in 1980, but remained almost constant after 1980. By 1985, 100 million school-age children in developing countries were not in school. About 70 percent of these were in the lowest-income countries, 45 percent in South Asia (India, Pakistan, and Bangladesh) and 30 percent in Sub-Saharan Africa. Most were in rural areas and about 60 percent were girls.
6.10 The enrollment gap between lower-income and higher-income countries is even more obvious at higher levels of education. In secondary education, gross enrollment rates increased most rapidly in the highest income countries, to 85 percent in 1985. This compared Education and Development: Evidence for New Priorities 69 to 64 percent in upper middle-income countries, 41 percent in lower middle-income, and 19 percent in low-income countries. In 1960, the gap was considerably less than in 1985. At the tertiary/university level, the 1985 enrollment rates ranged from 32 percent in the high- income countries, to 17 percent in high middle-income countries, 13 percent in low middle- income countries, and 2 percent in low-income countries, indicating the vast difference in access to higher education in countries at different levels of development. In part, the differences in secondary and higher enrollment reflect rational investment decisions based on different production structures, the derived demand for skills, and the pay-off to various levels of education. But such differences also imply highly differentiated capacities to take advan- tage of knowledge-based product and process innovations in all economic sectors. Those innovations hold the key to long-term welfare.
6.11 The gap between low-income and middle- and upper-income countries is most ominous in female and rural education. Past growth in enrollments has benefitted girls as well as boys, and girls represented a relatively high 40 percent of total enrollment in primary school in low-income countries in 1984 (as compared to 49 percent in middle- and higher-income countries). But this proportion drops off much more quickly at secondary and tertiary levels in low-income than in higher-income countries. This pattern is similar for rural young people. The worst off are rural girls in low-income societies. This lack of female education in rural, low-income societies may be a principal manifestation and reproducer of underdevelopment.
6.12 In addition to rising differences in enrollment rates and attainment levels, the knowledge gap may also be increasing in terms of educational quality. In 1960, the OECD countries spent 14 times more per student than low-income developing countries eligible for IDA loans. By 1980, the industrial nations were spending 50 times more per student than low- income countries. To the extent that the amount and nature of purchased inputs to educational processes are reflected in leaming outcomes, this trend is ominous.
6.13 In more direct fashion, several international studies, comparing and analyzing differences in student achievement across many countries, document what is perhaps the most serious problem facing schools in developing countries: the apparent difficulty of communi- ties, families, and schools to create an environment in which students can learn effectively. The studies show that students from industrial and newly industrializing countries greatly outperform students from lower-income countries on standardized achievement tests in read- ing, mathematics and science.
6.14 Students in developing countries' schools are therefore not only getting fewer years of education but are learning less in each of those years than students in higher-income countries. This is partly reflected in high repetition rates in primary and secondary schools. But even those who go straight through their school years are leaming less language skills, mathematics, and science in low-income and most middle-income countries than in the newly- industrialized developing countries (NICs) and the industrialized countries. Since these competencies are fundamental to self-efficacy and developing flexible skills in today's rap- idly-changing, industrializing environments, poor quality schooling has serious implications for a country's future ability to compete economically.
6.15 This is not to imply that only low-income countries are having difficulties in science and math education. Although students in the United States, for example, have high levels of scientific knowledge compared to most, a recent study reports that a low 7 percent of 17-year- olds were adequately prepared for college science courses, down from 8.5 percent in 1977.
Nations Face a Variety of Educational Problems Demanding Different Strategies
6.16 As successful participation in the world economy becomes more knowledge-inten- sive, all nations face the challenge of improving their educational systems. To varying degrees, all societies: (i) need to bring their education up-to-date in transmitting knowledge 70 Education and Development: Evidence for New Priorities and skills for dealing with the problems of the future; (ii) need to equalize access to high quality schooling; (iii) need to raise the level of math, language and science acquisition; (iv) need to improve the effectiveness of educational resources; (v) need to develop new approaches to schooling the disadvantaged; and (vi) need to develop mechanisms for the generation, acquisition, and application of appropriate knowledge.
6.17 But not all countries -- and not even all developing countries -- face the same educa- tional problems. Different educational and financial strategies are therefore appropriate to these widely differing conditions.
6.18 The highly industrialized countries, such as Japan, the United States, Canada, and most Westem European economies, have by and large achieved universal secondary education and send a significant percentage of young people through university. They devote a relatively high percentage of their GNP to education. Almost all these countries consider that in the new context of international competition, with its emphasis on scientific innovation and creative management, educational quality -- as measured by learning outcomes -- at all levels of schooling requires close attention. For example, the United States is very concerned that its science and math education in the lower grades is not as good as in other major industrial economies, with important future consequences for its leadership in high tech innovation. The education of the disadvantaged (e.g. immigrants, low-income groups) at all levels of schooling is important enough in some countries to be of major concern as well. But because they are leaders in scientific innovation and their economic development depends on translating this innovation into higher productivity and new products, the industrialized countries are especially concerned with the relationship between higher education (training), scientific research, and the application of research results and training to the production of goods and services (technological diffusion). For these countries, finding the most effective model for building research capacity and high level training and linking them for commercial applica- tions has a potentially enormously high payoff in increased economic growth.
6.19 A number of newly-industrialized developing countries (NICs), such as Mexico, Taiwan, and the Republic of Korea, and high-income oil producers, such as Saudi Arabia and Venezuela, have been generally successful in expanding their educational systems consistent with their economic and social development needs. In part this has been the result of good fortune (large oil reserves) or good public management in successfully mobilizing overall investment for economic growth. Most Asian countries, for example, have not had the fman- cial constraints caused by slow economic growth in the 1980s, as is now typical in Sub- Saharan Africa and Latin America. This educational expansion has also been the result of a strong commitment to education as a fundamental building block of the development process. These more rapidly developing economies -- like the developed countries -- are capable of mobilizing domestic resources to increase the quantity and quality of education and vocational training, but still need to make efficient and effective investments at all schooling levels and in vocational training programs in order to sustain growth and equalize access to knowledge. They need to develop strong scientific and technical education to consolidate and then improve their competitive position in a changing world economy. Some are beginning to innovate and therefore, like the highly industrialized countries, are concerned about linking university train- ing to research and to local industrial and service applications. Many of these countries must also confront educational inequities, particularly in female education and the education of lower-income students. But they are meeting the needs of the population for basic education, literacy is high, and many are well on the way to achieving a highly skilled labor force.
6.20 Many middle-income countries (for example, Colombia, Peru, the Philippines, Thai- land) and some large, low-income countries (China and, to a lesser extent, India, for example) have essentially achieved universal primary schooling and have rapidly increased secondary and university enrollment. By focusing on new technologies and increasing their telecommu- Education and Development: Evidence for New Priorities 71 nications and computer infrastructure, they are trying to transform their industries to play a more advanced role in the newly emerging world division of labor. The most important educational problems of these industrializing, middle-income, 'high" education countries revolve around improving the quality of primary education (especially reducing dropouts and increasing learning) and expanding and improving secondary and university education -- particularly making it relevant for high tech development. They must make important deci- sions regarding vocational versus academic education, the introduction of new kinds of scien- tific, mathematical, information technology and technology management programs into their secondary and university curricula, research and development funding for universities, and new linkages between universities and industry and agriculture.
6.21 Countries in a fourth group have some industries or have high value exports and could industrialize. These include most of the Central American countries, some Sub-Saharan Africa countries such as CMte d'Ivoire, Nigeria, and Botswana, for example, and countries such as Pakistan. They conceivably could fit into the world's new industrializing process if they can improve and expand their knowledge base and labor skills and begin to focus on appropriate technological strategies. They often face financial constraints, high dropout rates in primary schools, wide knowledge gaps within their societies (urban and rural, girls and boys), and rapidly increasing school-age populations. These countries are concerned with secondary and university educational reforms for the information revolution, but also have to focus on basic education for reduced fertility, better health care and nutrition, and higher agricultural productivity. They must make fundamental improvements in the quality of basic education and may, in many cases, have to develop improved delivery strategies at the primary level to achieve universality and higher quality.
6.22 A fifth set of countries is still primarily agricultural, grappling with providing basic education to their population. Many Sub-Saharan Africa countries fall into this category, as well as Afghanistan, Bangladesh, and Nepal. They face severe financial and human resource constraints in developing their educational systems. At the same time, the information and biotechnology revolutions are placing increased pressures on them to produce cadres of highly-trained scientific and management personnel, as well as the highly productive skilled and semi-skilled workers that will give them some chance of participating in the new world economic system. Their basic education must receive primary attention, with increased focus on highly efficient ways of delivering the necessary literacy, math and science skills to the mass of their rural populations, including involving more community resources in primary education and greatly improving the level of teaching and school management.
6.23 These low-income economies face a whole different set of educational problems, beginning with difficulties in providing minimal basic education for a rapidly growing primary school population, achieving universal literacy, and developing adequate skills to raise low standards of living in rural and urban areas. Lack of financial resources, growing school-age population, skill shortages, and the inefficient use of resources are all barriers to educational expansion. Annual per capita GDP growth in low-income countries (excluding India and China) dropped from 0.6 percent in 1965-80 to 0.4 percent in 1980-86; and in low middle- income countries, from 3.8 percent in 1965-80 to -0.8 percent in 1980-86, although there was considerable variation in the latter group. Low-income countries (excluding India and China) had reached a per capita income of only US$200 in 1986. They spent the lowest proportion of their GDP on education - and this proportion declined from a high of 3.3 percent in 1975 to less than 3 percent in the 1980s. In these countries, teaching and management skills are in very short supply, and funds for education are lacking. The very nature of these problems is different from those of education in higher-income countries.
6.24 New educational approaches are important for all countries but urgent for those facing severe financial constraints. Poorer countries are increasingly less able financially to 72 Educationand Development: Evidencefor New Priorities catch up using wasteful, poorly managed educational delivery systems that have little linkage with the community they are supposed to serve. In such economies, where high quality educational resources are extremely scarce, teachers have to draw effectively on the surround- ing community to create an active learning environment and a problem-solving approach to math and science. Teacher and school management training should incorporate such methods as part of their curriculum. New financial approaches are also more urgent, especially for higher-cost secondary and higher education. The low-income countries spend much more per university student, relative to GNP per capita, than the industrialized countries or the NICs.
6.25 At the same time, low-income countries (like middle-income countries and the NICs) need to develop the scientific personnel who will understand fully the latest technological advances coming out of the industrialized countries and be able to adapt and apply them for local production of goods and services. These countries must therefore also be concemed about delivering high-quality university education -- even for a relatively small number of youth -- and its relationship to research and development, especially for the packaging of new (and old) technologies for local applications. Bibliography
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Education and Poverty: General
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The Educational Spending Crisis: General
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Inoue, K. The Education and Training of Industrial Manpower in Japan. World Bank Staff Working Paper No. 729, Washington, D.C.: World Bank, 1985.
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The Quality and Efficiency of Education: General
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Coleman, J., et. al. High School Achievement: Public, Catholic and Private Schools Com- pared. New York: Basic Books, 1982. 88 Education and Development: Evidence for New Priorities
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Carnoy, M., R. Sack and H. Thias. Determinants and Effects of School Performance: Secondary Education in Tunisia. Washington, D.C.: World Bank, 1977.
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Zuzovsky, R. 'Home and School Contributions to Science Achievement in Israel." Washington, D.C.: World Bank, PHREE, 1987, (mimeo).
Technology in Education: General
Anzalone, S. Project Bridges: Hardwarefor Primary Education in Developing Countries: A Review of the Literature. Harvard University, 1987.
Asian Development Bank. Distance Education, Vols. I and II, 1986.
Becker, H. The Impact of Computer Use on Children's Learning. Baltimore: Johns Hopkins University Press, 1987.
Block, C. 'Interactive Radio and Educational Development: An Overview." Developing Communications Report. (49), 1985.
Camoy, M., et. al. Education and Computers: Visions and Realities in the Mid-1980s. Stanford: Stanford University, 1986.
Camoy, M. and L. Loop. Computers and Education: WhichRole for International Research? Paris: UNESCO, 1986.
Carnoy, M. 'The Economic Costs and Returns to Educational Television," in Arnove, R. F. (ed.), Educational Television: A Policy Critique and Guidefor Developing Countries. New York: Praeger, 1976.
Clearinghouse on Development Communication. "Project Profiles," Washington, D.C.: Clearinghouse on Development Communications, 1982.
Freeman, C. Computer Classroom Ethnography: Crochu Primary School, Grenada. McLean, Virginia: Institute for International Research, Learning Technologies Project, 1987.
Friend, J. and S. Kozlow. Evaluation of Second Grade Instructional Materials Produced by the Radio-assisted Community Basic Education Project. Washington, D.C.: Inter-American Research Associates, 1985.
Jamison, D. and E. McAnany (eds.). Radio for Education and Development. Beverly Hills: Sage, 1978.
Kaye, A. "The Ivory Coast Educational Television Project," in Arnove, R. (ed.), Educational Television, 1976.
Kulik, J., C. Kulik and R. Bangert-Drowns. "Effectiveness of Computer Based Education in Elementary Schools." Journal of Computers in Human Behaviour 1:59-74, 1985.
Levin, H. M., et. al. Improving Productivity Through Education and Technology. Stanford: CERAS, 1984.
Mayo, J., et. al. Educational Reform With Television: The El Salvador Experience.Stanford: Stanford University, 1976.
Ministry of Education, Ethiopia. Evaluation of Primary School Radio Programs. Addis Ababa, 1987. Education and Development: Evidence for New Priorities 93
Neurath, P. Radio Farm Forums in India. New Delhi: Government of India Press, 1960.
Oxford R., et. al. Final Report: Evaluation of the Kenya Radio Language Arts Project, Vol. I: Narrative Results. Washington, D.C.: Academy for Educational Development, 1986.
Papagianis, G. Information Technology and Education. Ottawa: Intemational Development Research Centre, 1987.
Roblyer, M., W. Castine and F. King. 'The Effectiveness of Computers in Instruction: A Review and Synthesis of Recent Research Findings," 1987 (Submnittedfor Publication).
Schramnm,W., et. al. Bold Experiment: The Story of Educational Television in American Samoa. Stanford, CA: Stanford University, 1981.
Schramnm,W. (ed.). New Educational Media in Action: Case Studies for Planners. Paris: UNESCO, HEP, 1967.
Shukla, P. Satellite Instructional TV Experiment in India. As cited in Anzalone, 1987.
Suppe, P., B. Searle, et. al. The Radio Mathematics Project, Nicaragua. Stanford, CA: Stanford University Press, 1978.
UNESCO. New Educational Media in Action: Case Studies for Planners, Vols. I and II. Paris: UNESCO, IIEP, 1976.
UNESCO. The Economics of New Educational Media: Cost and Effectiveness, Vols. I and 11. Paris, 1984, Media Education. Paris, 1980.
Walker, H. Evaluacion Cualitiva del Programa de Radioeducacion Comunitaria (RADECO) de la Republica Dominicana. Washington, D.C.: USAID, 1986.
Williams, K. 'Computers in Trinidad and Tobago: A Survey of Access and Attitudes Towards the Technology in Secondary Schools." Doctoral Dissertation. Cambridge, Massachusetts: Harvard University.
Technology in Education: What the Bank Has Done
Anzalone, S. 'Educational Technology and the Improvement of General Education in Devel- oping Countries." Washington, D.C.: World Bank, PHREE 1988 (mimeo).
Cassirer, H. "Radio in an African Context: A Description of Senegal's Pilot Project." in P. Spain, et al., Radio for Education and Development. Washington, D.C.: World Bank, 1977.
Feliciano, G., et. al. The Educational Use of Mass Media. World Bank Staff Working Paper No. 491, Washington, D.C.: World Bank, 1981.
Nettleton, G. "Uses and Costs of Educational Technology for Distance Education in Develop- ing Countries: A Review of the Recent Literature." Washington, D.C.: World Bank (forth- coming)
Hawkridge, D. General Operational Review of Distance Education. EDT Discussion Paper No. 68, Washington, D.C.: World Bank, 1987. 94 Education and Development: Evidence for New Priorities
Hall, B. and T. Dodds. 'Voices for Development: The Tanzania National Radio Study Campaign" in P. Spain, et al., Radio for Education and Development. Washington, D.C.: World Bank, 1977.
Hudson, H. "Community Use of Radio in the Canadian North." in P. Spain, et al., Radio for Education and Development. Washington, D.C.: World Bank, 1977.
Jamison, D. Radio Education and Student Repetition in Nicaragua. World Bank Reprint Series No. 91, Washington, D.C.: World Bank, 1978.
Levin, H. 'Educational Production Theory and Teacher Inputs" in C. Bidwell and D. Windham (eds.), The Analysis of Productivity: Issues in Macro Analysis. Cambridge, Mass.: Ballinger Publishing, 1980.
Perraton, H. (ed.). Alternative Routes to Formal Education. Baltimore: Johns Hopkins University, 1982.
Perraton, H. (ed.). Distance Education: An Economic and Educational Assessment of its Potentialfor Africa. EDT Discussion Paper No. 43, Washington, D.C.: World Bank, 1986.
Perrett, H. Using Communication Support in Projects. World Bank Staff Working Paper No. 551, Washington, D.C.: World Bank, 1982.
Spain, P. (ed.). Radio for Education and Development: Case Studies. World Bank Staff Working Paper No. 266, Washington, D.C.: World Bank, 1977.
Tiene, D. and S. Futagami. Educational Media in Retrospect. EDT Discussion Paper No. 58, Washington, D.C.: World Bank, 1987.
White, R. "Mass Communications and the Popular Promotion Strategy of Rural Development in Honduras," in Spain, P. L., et. al., Radio for Education and Development, Vol. II. Washington, D.C.: World Bank, 1977.
Sector Management General
Figueroa, M. Methodological Explorations on Schooling and the Reproduction of the Social Division of Labor: A Case Study of Mexico City. Doctoral dissertation, Stanford University, 1986.
Goodlad, J. A Place Called School. New York: McGraw-Hill, 1984.
Kulakow, A. M., et. al. Mobilizing Rural Community Resources for Support and Develop- ment of Local Learning Systems in Developing Countries. Washington, D.C.: Academy for Educational Development, 1978.
Meyer, J. "The Charter: Conditions of Diffused Socialization in Schools," in Scott, R. (ed.), Social Processes and Social Structures. New York: Holt, Rinehart and Winston, 1970.
Morales, J. and A. Pinellsiles. 7he Determinant Factor and the Costs of Bolivia. Working Paper No. 4-77. La Paz: Universidad Catolica Boliviana, 1977.
Meyer, J., et. al. Bureaucratization Without Centralization: Changes in the Organizational System of American Public Education, 1940-1980. Palo Alto: CERAS, Stanford University, 1985. Education and Development: Evidence for New Priorities 95
National Commission on Excellence in Education. A Nation At Risk Washington, D.C.: Government Printing Office, 1983.
Sembiring, R. and I. Livingstone. National Assessment of Quality of Indonesian Education. Ministry of Education and Culture, Jakarta, Indonesia, 1981.
Sector Management: What the Bank Has Done
Auerhan, J., et. al. A Study of Institutional Development in Education and Training in Sub- Saharan African Countries. EDT Discussion Paper No. , Washington, D. C.: World Bank, November 1985.
Craig, J. Implementing Educational Policies in Sub-Saharan Africa, A Review of the Litera- ture. EDT Discussion Paper No. 79, Washington, D.C.: World Bank, May 1987.
Fullan, M. "Implementing Educational Change - What We Know." PHREE Background Paper No. 89/18, Washington, D.C.: World Bank, 1989.
Fuller, B. "What School Factors Raise Achievement in the Third World?" Review of Educa- tional Research (57)3, 1987.
Fuller, B. and M. Lockheed. Policy Choice and School Efficiency in Mexico: An Analysis of the Impact of National Policy Decisions on Student Achievement. EDT Discussion Paper No. 78, Washington, D.C.: World Bank, May 1987.
Haddad, W., et. al. "A Conceptual Framework for Policy Analysis," 1987. (mimeo)
Heyneman, S. and W. Loxley. 'The Effect of Primary School Quality on Academic Achieve- ment Across 29 High- and Low-Income Countries." American Journal of Sociology. (88)6, 1983.
James, E. The Political Economy of Private Education in Developing Countries. EDT Discussion Paper No. 71, Washington, D. C.: World Bank, May 1987.
Jimenez, E. and J. Tan. Decentralized and Private Education: The Case of Pakistan, EDT Discussion Paper No. 61, Washington, D. C.: World Bank, 1988.
Jimenez, E., et. al. The Relative Effectiveness of Private and Public Schools in Enhancing Achievement: The Case of Thailand. EDT Discussion Paper No. 97, Washington, D. C.: World Bank, June 1987.
Middleton, J., James Terry and Deborah Bloch. Building Educational Evaluation Capacity in Developing Countries. PPR Working Paper No. 140. Washington, D.C.: World Bank, 1989.
Middleton, J., H. Woldemariam and C. Mayo-Brown. Management in World Bank Education Projects: Analysis of Experience. EDT Discussion Paper No. 42, Washington, D.C.: World Bank, 1986.
Middleton, J., D. Rondinelli and A. Verspoor. Designing Managementfor Uncertainty and Innovation in Education Projects. EDT Discussion Paper No. 75, Washington, D. C.: World Bank, April 1987.
Noor, A. A General Operational Review: "Strengthening Educational Management: A Review of World Bank Assistance," 1985. (mimeo) 96 Education and Development: Evidence for New Priorities
Somerset, H. Case Study on Examinations Reform: The Kenya Experience, 1983. EDT Discussion Paper No. 64, Washington, D. C.: World Bank, 1987.
Verspoor, A. Project Management for Educational Change. EDT Discussion Paper No. 12, Washington, D.C.: World Bank, 1985.
Verspoor, A. Implementing Educational Change: The World Bank Experience. EDT Discussion Paper No. 44, Washington, D.C.: World Bank, 1986.
Winkler, D. 'Decentralization in Education. An Economic Perspective." PPR Working Paper No. 143, Washington, D.C.: World Bank, 1989.
Science Education: General
King, K. (ed.). Science Education and Society: Perspectives from India and South East Asia. Ottawa: International Development Research Centre, 1985.
Morris, R.W. (ed.). Science and Technology Education and National Development. Paris: UNESCO, 1983.
Raizen, S. Increasing Educational Productivity Through Improving the Science Curriculum. New Brunswick, NJ: Rutgers University, Center for Policy Research in Education, 1988.
Suppe, P., et al., The Radio Mathematics Project: Nicaragua. Stanford: Stanford University Press, 1978.
U.S. Congress, Office of Technology Assessment. Special Report on Information Technology and Education. Washington, D.C.: U.S. Government Printing Office, 1988.
Science Education: What the Bank Has Done
Haddad, W. and G. Za'rour. Role and Educational Effects of Practical Activities in Science Education. EDT Discussion Paper No. 51, Washington, D. C.: World Bank, 1986.
Higher Education and Technology Transfer: General
Asian Development Bank. Distance Education: Volumes I and n. Manila: Asian Develop- ment Bank, 1986.
Bianchi, P., M. Camoy and M. Castells. Economic Reform and Technology Transfer in China. Stanford University: CERAS, 1988.
Carnoy, M. "High Technology and Education: An Economist's View." in Society as Educa- tor in an Age of Transition. Chicago: National Society for the Study of Education, 1987.
Coleman, J.S., et al., High School Achievement: Public, Catholic and Private Schools Compared. New York: Basic Books, 1982.
Edquist, C. Capitalism. Socialism and Technology: A Comparative Study of Cuba and Jamaica. London: Zed, 1985. Education and Development: Evidence for New Priorities 97
Edquist, C. and S. Jacobsson. Flexible Automation: The Global Diffusion of New Technolo- gies in the Engineering Industry. London: Basil Blackwell, 1988.
National Science Foundation. Science and Engineering Education for the 1980s and Beyond. Washington, D.C.: NSF, Department of Education, 1980.
Ritter, U. Higher Education by the Year 2000. New York, Campus Publications, 1985.
Rosenberg, N. Inside the Black Box. Cambridge: Carnbridge University Press, 1982.
U. S. House of Representatives, Conmnittee on Science and Technology (98th Session). U.S. Science and Engineering Education and Manpower. Washington, D.C.: U. S. Govermment Printing Office, 1983.
Useem, E. Low Tech Education in a High Tech World. New York: Free Press, 1986.
Higher Education and Technology Transfer: What the Bank Has Done
Bowman, M., B. Millot and E. Schiefelbein. The Political Economy of Higher Education: Studies in Chile, France and Malaysia. EDT Discussion Paper No. 30, Washington, D.C.: World Bank, 1986.
Hinchliffe, K. Issues Related to Higher Education in Sub-Saharan Africa. World Bank Staff Working Paper No. 729, Washington, D.C.: World Bank, 1985.
Perraton, H. Alternative Routes to Formal Education: Distance Teaching for School Equivalency, Baltimore: Johns Hopkins University Press, 1982.
Weiss, C. 'Science and Technology and the World Bank," July 1983. (mimeo)
Za'rour, G. Status of Universities in the Arab Countries of the Middle East and North Africa. PPR Working Paper No. 62, Washington, D.C.: World Bank, 1988.
Educational Finance Reform: General
Armitage, J. and R. Sabot. "Efficiency and Equity Implications of Subsidies of Secondary Education in Kenya," in Newberry, D. and N. Stem (eds.), Modern Tax Theories For Develop- ing Countries. New York: Oxford University Press, 1985.
Gustafsson, I. Work as Education - Perspectives on the Role of Work in Current Educational Reform in Zimbabwe. Oxford: Pergamon Press, 1988.
Eicher, J. C. Educational Costing and Financing in Developing Countries. Staff Working Paper No. 655, Washington, D.C.: World Bank, 1984.
Hansen, W. and B. Weisbrod. Benefits, Costs and Finance of Public Higher Education. Chicago: Markham Publishing Company, 1969.
Heller, P. and A. Cheasty. 'Sectoral Adjustment in Government Expenditure in the 1970s: The Education Sector in Latin America." World Development. (12), 1984. 98 Education and Development: Evidence for New Priorities
Kulakow, A., et al. Mobilising Rural Community Resources for Support and Development of Local Learning Systems on Developoing Countries. Washington, D.C.: Academy for Educational Development, 1978.
Levin, H. New Schools for the Disadvantaged. Stanford: CERAS, 1987.
Levin, H. "Education As A Public and Private Good." Journal of Policy Analysis. (6), 1987.
Meeth, L. R. A Curricular and Financial Cost Analysis of the Independent Two Year College of America. Washington, D.C.: National Council of Independent Junior Colleges, 1974.
Smock, A. Women's Education in Developing Countries: Opportunities and Outcomes. New York: Praeger, 1981.
Yao Yao, J. "The Redistribution of Earnings in the Ivory Coast: The Role of Higher Education Finance." Doctoral Dissertation, Stanford University, 1987.
Educational Finance Reform: What the Bank Has Done
Castenada, T. Innovations in the Financing of Education: The Case of Chile. EDT Discussion Paper No. 35, Washington, D.C.: World Bank, 1986.
Eicher, J. C. Educational Costing and Financing in Developing Countries. World Bank Staff Working Paper No. 655, Washington, D.C.: 1984.
Hinchliffe, K. Federal Finance, Fiscal Imbalance and Educational Inequality. EDT Discus- sion Paper No. 72, Washington, D.C.: World Bank, 1987.
Hultin, M. and J. P. Jallade. Costing and Financing Education in LDCs: Current Issues. World Bank Staff Working Paper No. 216, Washington, D.C.: World Bank, 1975.
Jallade, J. P. Public Expenditures on Education and Income Distribution in Colombia. Baltimore: Johns Hopkins University Press, 1974.
Jallade, J. P. Student Loans in Developing Countries: An Evaluation of Colombian Perform- ance. World Bank Staff Working Paper No. 182, 1974.
Jallade, J. P. Poverty Alleviation and Educational Lending: Present Practice and Future Prospects. Washington, D.C.: World Bank, 1982.
Jallade, J. P. Financing of Education: An Examination of Basic Issues. World Bank Staff Working Paper No. 157, Washington, D.C.: World Bank, 1973.
Jimenez, E. Pricing Policy in the Social Sectors: Cost Recovery for Education and Health in Developing Countries. Baltimore: Johns Hopkins University Press, 1987.
Jimenez, E. 'Structure of Educational Costs: Multiproduct Cost Funcations for Primary and Secondary Schools in Latin America." Economics of Education Review. 5, 1986.
Jimenez, E., M. Lockheed and N. Wattananwaha. `The Relative Efficiency of Private and Public Schools: The Case of Thailand. The World Bank Economic Review. (2)2, 1988. Education and Development: Evidence for New Priorities 99
Mingat, A. and J. P. Tan. "Expanding Education Through User Changes in LDCs: What Can Be Achieved?" Economics of Education Review 5(3), 1986.
Psacharopoulos, G., 'Economics of Higher Education in Developing Countries." Comparative Economic Review. (26)2 1982.
Psacharopoulos, G., Economics of Education. Oxford: Pergamon Press, 1987.
Psacharopoulos, G., "Curriculum Diversification, Cognitive Achievement and Economic Per- formance: Evidence from Colombia and Tanzania." in J. Lauglo and K. Lillis (eds.), Voca- tionalising Education. Oxford: Pergamon Press, 1988.
Psacharopoulos, G., J.P. Tan and E. Jimenez. The Financing of Higher Education in Latin America: Issues and Lines of Action. EDT Discussion Paper No. 32, Washington, D.C.: 1986.
Schiefelbein, E. Education, Costs and Financing Policies in Latin America. EDT Discussion Paper No. 60, Washington, D.C.: World Bank, 1985.
Tan, J. P., et. al. User Chargesfor Education: The Ability and Willingness to Pay in Malawi. World Bank Staff Working Paper No. 661, Washington, D.C.: World Bank, 1984.
Wolff, L. Controlling the Cost of Education in Eastern Africa. World Bank Staff Worldng Paper No. 702, Washington, D.C.: World Bank, 1984.
Woodhall, M. Student Loans as a Means of Financing Higher Education: Lessons from International Experience. World Bank Staff Working Paper No. 599, Washington, D.C.: World Bank, 1983.
World Bank. Financing Education in Developing Countries: An Exploration of Policy Options. Washington, D.C.: World Bank, 1986. Distributors of World Bank Publications
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JIm_busg 3024 Recent World Bank Discussion Papers (continued)
No. 65 DevelopingEconomies in Transition.Volume III: CountryStudies. F. Desmond McCarthy, editor
No. 66 IllustrativeEffects of VoluntaryDebt and Debt ServiceReduction Operations. Ruben Lamdany andJohn M. Underwood
No. 67 Deregulationof Shipping: MhatIs to Be LeamedfromChile. Esra Bennathan with Luis Escobar and George Panagakos
No. 68 PublicSector Pay and EmploymentReform: A Reviewof WorldBank Experience.Barbara Nunberg
No. 69 A MultilevelModel of SchoolEffectiveness in a DevelopingCountry. Marlaine E. Lockheed and Nicholas T. Longford
No. 70 UserGroups as Producersin ParticipatoryAfforestation Strategies. Michael M. Cemea
No. 71 HowAdjustment Programs Can Help the Poor: The WorldBank's Experience.Helena Ribe, Soniya Carvalho, Robert Liebenthal, Peter Nicholas, and Elaine Zuckerman
No. 72 Export Catalystsin Low-IncomeCountries: A Review of ElevenSuccess Stories. Yung Whee Rhee and Therese Belot
No. 73 InformationSystems and BasicStatistics in Sub-SaharanAfrica: A Review and StrategyforImprovement. Ramesh Chander
No. 74 Costsand Benefitsof Rent Controlin Kumasi, Ghana. Stephen Malpezzi, A. Graham Tipple, and Kenneth G. Willis
No. 75 Ecuador'sAmazon Region:Development Issues and Options.James F. Hicks, Herman E. Daly, Shelton H. Davis, and Maria de Lourdes de Freitas [Also availablein Spanish (75S)]
No. 76 Debt Equity ConversionAnalysis: A Case Study of the PhilippineProgram. John D. Shilling, Anthony Toft, and Woonki Sung
No. 77 HigherEducation in LatinAmerica: Issues of Efficiencyand Equity. Donald R. Winkler
No. 78 The GreenhouseEffect: Implicationsfor Economic Development. Erik Arrhenius and Thomas W. Waltz
No. 79 Analyzing Taxes on BusinessIncome with the MarginalEffective Tax Rate Model.David Dunn and Anthony Pellechio
No. 80 EnvironmentalManagement in Development:The Evolutionof Paradigms.Michael E. Colby
No. 81 Latin America'sBanking Systems in the 1980s:A CrossCountry Comparison. Felipe Morris, Mark Dorfman, Jose Pedro Ortiz, and others.
No. 82 Why EducationalPolicies Can Fail: An Overviewof SelectedAftican Experiences. George Psacharopoulos
No. 83 ComparativeAfrican Experiences in ImplementingEducational Policies. John Craig
No. 84 ImplementingEducational Policies in Ethiopia.Fassil R. Kiros
No. 85 ImplementingEducational Policies in Kenya. G. S. Eshiwani
No. 86 ImplementingEducational Policies in Tanzania. C. J. Galabawa
No. 87 ImplementingEducational Policies in Lesotho.T. Sohl Thelejani
No. 88 ImplementingEducational Policies in Swaziland.Cisco Magalula
No. 89 ImplementingEducational Policies in Uganda.Cooper F. Odaet
No. 90 ImplementingEducational Policies in Zambia. Paul P. W. Achola
No. 91 ImplementingEducational Policies in Zimbabwe.0. E. Maravanyika
No. 92 InstitutionalReforms in SectorAdjustment Operations: The WorldBank's Experience.Samuel Paul
No. 93 Assessmtentof the PrivateSector: A CaseStudy and Its MetlhodologicalItuplications. Samuel Paul
No. 94 Reachingthe Poorthrough Rural PublicEmployment: A Surveyof Theoryand Evidence.Martin Ravallion The World Bank Headquarters European Office Tokyo Office 1818 H Street, N.W. 66, avenue d'l&na Kokusai Building Washinigton,D.C. 20433, U.S.A. 75116 Paris, France 1-1 Marunouchi 3-clome Chivoda-ku, Tokyo 100,Japan Tclephone: (202) 477-1234 Telephone: (1) 40.69.30.00 Facsimile:(202) 477-6391 Facsimile:(1) 47.20.19.66 Telephone: (3) 214-5001 Telex: wuI 64145 WORLDBANK Telex: 842-620628 Facsimile:(3) 214-3657 RCA 248423 WORLDBK Telex: 781-26838 Cable Address: INTBAFRAD WASHINGTONDC
ISBN 0-8213-1624-9